We were forwarded the blurb below. Essentially, build our product for us and we'll take 82% of the equity because we came up with the idea. I was much amused-
HAAS TEAM IN SEARCH OF ENGINEER!
We are a group of 5 Haas students who are currently in a process of developing a p2p mobile app. We have already recruited a team of interns who are eager to start working under the leadership of a new VP of Engineering.
We have skills in marketing, interface design, business development, investment research, and statistical analysis.
New *** venture, ******, seeks Cofounder/VP Engineering to spearhead development of a mobile software platform with peer-to-peer functionality. This is a straightforward project and we are aiming to get an efficiently working prototype completed by the week of Nov 22. We have proof of concept and market research. Now we simply need to build and sell. We are advised by a founder of Berkeley's CET and a venture capitalist, who also teaches at Cal.
Compensation is a 1/6 share of total equity in a pool of five other founders!
You should be passionate about programming, able to demonstrate your skills, and ready to work as a team to grow a successful startup in the sharing economy (i.e. Lyft, AirBnB, ZipCar).
Skills needed:
- demonstrable experience with coding mobile software
- experience with peer-to-peer functionality
- ability to develop application for both Android and iOS
- ability to build and lead a software development team (of interns to start)
- willingness to follow Agile development process
- self-motivated, sense of urgency
- team mentality, results oriented, goal driven
- strong time management skills and ability to commit to co-located work hours
- as cofounder, ability to work in a business development team to grow the company quickly
- excellent communication skills
- true passion for the startup environment and building mobile apps
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- Posts tagged 'berkeley'
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As I mentioned previously, I was offered the fantastic opportunity to give Neal Stephenson a lift to Oakland airport on his way home after a panel session at UC Berkeley. Rather than asking him about something particular to his work, I thought I'd ask him about how he gets stuff done. It's a topic that I'm continuously fascinated with - being both a complete data junkie and a pathological procrastinator. As an author who is clearly very productive, I was curious as to how he does it. Accompanying me was Constantin, a PhD student at UC Berkeley.
Turns out the treadmill desk in REAMDE wasn't entirely fictional - Neal actually uses one of these to work on. Apparently a low walking speed makes it possible to type and work. A wrist rest is necessary to dampen the side to side rocking of your wrists as you walk. For work where he's handwriting, he uses a standing desk (since it's not possible to handwrite while walking).
I previously noted the curious coffee shop culture in the US and was curious if Neal adhered to the cafe-author stereotype. He mentioned that he didn't - preferring an atmosphere of quiet and to stay in one place (I recall libraries being mentioned). If he needs to use a lot of his notes and materials, he needs to be at home with a desk to lay things out.
Generally he doesn't like travelling to speaking arrangements since it can be quite disruptive to getting work done. Not only the actual time spent travelling and speaking but also the communication overhead that goes into organising an event.
He works in the morning normally - and stops as soon as he feels his alertness tailing off. Most of the time he writes a paragraph well enough the first time. As he said, 'editing a work of literature is like performing surgery on a human body. There are always scars and seams left over.'
All of his work eventually hits a computer - either in LaTeX or, lately, using Mac writing application Scrivener. Occasionally he'll handwrite work - work that is handwritten tends to be better thought through since there's a longer buffer between his thoughts and putting them to paper (since handwriting is slower).
I asked him how he felt about this world of push notifications - where we are pinged quickly with every new bit of information - tweet, news article or email. He says that he just has those turned off since his job doesn't require continuous notification. I would suggest that that's probably true of most jobs - we're just addicted to the small dopamine hit that accompanies each notification. Perhaps that will be the next life hack I try to implement.
With such incredibly intricate story lines and characters, I was curious how he organises his research. Supposedly he doesn't have a definitive scheme, preferring to keep notes organised randomly. This is apparently useful to allow ideas and notes to cross-pollinate others as he searches for the notes he wants.
Finally, I was curious how he keeps his work from getting eaten by his computer. Supposedly he backs up to a RAID in the basement and to a USB stick every two weeks.
On a final note - it was a pleasure to meet the man himself. I took a hiatus from reading serious amounts of fiction for most of my late teens, as I became more immersed in my cycling hobby. As I left Cambridge, I started reading fiction again and started off with his novels. I've not stopped since.
Work Environment
Turns out the treadmill desk in REAMDE wasn't entirely fictional - Neal actually uses one of these to work on. Apparently a low walking speed makes it possible to type and work. A wrist rest is necessary to dampen the side to side rocking of your wrists as you walk. For work where he's handwriting, he uses a standing desk (since it's not possible to handwrite while walking).
I previously noted the curious coffee shop culture in the US and was curious if Neal adhered to the cafe-author stereotype. He mentioned that he didn't - preferring an atmosphere of quiet and to stay in one place (I recall libraries being mentioned). If he needs to use a lot of his notes and materials, he needs to be at home with a desk to lay things out.
Schedules
Generally he doesn't like travelling to speaking arrangements since it can be quite disruptive to getting work done. Not only the actual time spent travelling and speaking but also the communication overhead that goes into organising an event.
He works in the morning normally - and stops as soon as he feels his alertness tailing off. Most of the time he writes a paragraph well enough the first time. As he said, 'editing a work of literature is like performing surgery on a human body. There are always scars and seams left over.'
Medium
All of his work eventually hits a computer - either in LaTeX or, lately, using Mac writing application Scrivener. Occasionally he'll handwrite work - work that is handwritten tends to be better thought through since there's a longer buffer between his thoughts and putting them to paper (since handwriting is slower).
On Notifications
I asked him how he felt about this world of push notifications - where we are pinged quickly with every new bit of information - tweet, news article or email. He says that he just has those turned off since his job doesn't require continuous notification. I would suggest that that's probably true of most jobs - we're just addicted to the small dopamine hit that accompanies each notification. Perhaps that will be the next life hack I try to implement.
Organisation
With such incredibly intricate story lines and characters, I was curious how he organises his research. Supposedly he doesn't have a definitive scheme, preferring to keep notes organised randomly. This is apparently useful to allow ideas and notes to cross-pollinate others as he searches for the notes he wants.
Backup
Finally, I was curious how he keeps his work from getting eaten by his computer. Supposedly he backs up to a RAID in the basement and to a USB stick every two weeks.
On a final note - it was a pleasure to meet the man himself. I took a hiatus from reading serious amounts of fiction for most of my late teens, as I became more immersed in my cycling hobby. As I left Cambridge, I started reading fiction again and started off with his novels. I've not stopped since.
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It's been just over 3 weeks since my last update and I've evidently failed to blog weekly as promised. It's hard to believe October is almost over. Fall (or Autumn) is definitely here now - leaves are falling and there are, on average, fewer hours of sunlight each day. The cold is sweeping in. As we started October the Berkeley 'Indian summer' carried over to give us a HOT first few days. This didn't persist much beyond the first weekend though and it quickly moved into 'hoody' weather.
Soon after that, I managed to accidentally smash my bedroom window while fitting my new amplifier and the nights became much cooler. This led to some very chilly nights, which became better when Ryan used his superior duct tape to actually seal the window with cardboard (versus just slotting it in - which was my approach).
Broken glass aside, it's been a monumentally busy month. The day after my last update, I went sea kayaking on the bay with Cal Adventures, the outdoor centre that is run by (affiliated with?) the university. This was a one day introductory course that allows me now to go out on the bay alone (within line of sight of the centre). While the pace of the course was a little slow for my liking, we were extremely lucky to catch such beautiful weather and being out on the bay was a peaceful experience that helped mitigate some of the stress of our second Advanced Robotics assignment.
The calm didn't last for long though because I was soon onto an assignment for Computer Vision. Once this was completed, I had an Advanced Robotics assignment that was due in a week. It had come out late beacuse our Professor had recently changed the questions and had been trying to solve them himself. This took longer than expected...perhaps an ominous sign. Logistics made it impossible to heed his advice that we start immediately and so I tried my best to do it in a week. This proved to be difficult - in the end taking 9 days (using all of my remaining late days).
During those 9 days, I put in about 50 hours of work, getting stuck on the last part of the first question for three days. Despite going to see our teaching assistant three times about it, I got no further. Bad strategy which resulted in me turning in the assignment 70% complete. Whoops. Looks like trying to juggle the job hunt with a graduate degree at Berkeley is a difficult optimisation problem!
This past week has been a bit of a rollercoaster for a number of reasons. After receiving one job offer, the other employers are reacting much more quickly and this next week I have 6 interviews planned. I'm wishing I hadn't scheduled my Google phone screen first - now that I've had numerous telephone screens, I might have screwed that one up much less badly.
A few weeks ago a professor sent around a request for volunteers to pick up/drop author Neal Stephenson from/to the airport. He came to a panel on campus, vaguely entitled 'On The Future: Beyond Computing'. Other members of the panel included Peter Norvig, Director of Research at Google and Jaron Lanier, author and coiner of the term 'virtual reality'. I capitalised on my free Zipcar credit and replied - a few hours after the email was sent around. It looks like my response time was favourable and I was tasked with dropping him off to Oakland airport on the day after the talk. Equally as exciting, Professor Katz invited me to dinner with the panelists afterwards. (Googling Professor Katz revealed him to be one of the creators of RAID. Incredible. I was very tempted to ask him if he knew where my data all went, that one time...)
This was an interesting experience, being both simultaneously over and underwhelming for reasons best explained in person. I'll post a separate note with my takeaways from my conversation with Neal Stephenson. Still, I was buzzing with excitement for a good two days after that. What struck me as most admirable was how normal these tremendously acclaimed people were. I'd always imagined that reaching their heights of 'notoriety' came with some ego inflation but meeting these three demonstrated how untrue that assumption was.
The next day we had the interview at the culmination of our application to Steve Blank's Lean Launchpad class. As I mentioned previously, this was one of the classes that helped me decide to come here and I was quite looking forward to it. The interview itself was short - which indicated that either we had enough information on our application or that they had already made up their mind. We'd put a lot of effort into our application, spending quite a bit of effort researching the space around our proposed 'startup' (similar to my capstone project). They asked questions around our idea and around our team for a total of 5 minutes before we were let free.
A double gin and tonic (or club soda, tonic is expensive here) plus 8.95 hours of sleep later, I woke up to a depressing rejection email from the teaching assistant for the class. We've yet to receive feedback as to our rejection which is strange, because they're normally very quick to queries. The silver lining is that I'll now have significantly more time next semester to sleep, exercise and submit applications for accelerators.
The last couple of days have been moderately alcoholic; after the last few weeks, I was desperate for some mindless social interaction. Yesterday we had our MEng Halloween party and it occurred to me that the primary reason people hold Halloween parties as adults here is to take photos. Despite buying $10 worth of cardboard sheets, some cyan spray paint and duct tape, I ran out of time and wasn't able to recreate a costume based on the Hype Dark robot. One day.
This coming 12 days is going to be the toughest of the semester yet. In addition to the 6 interviews, I have a couple of social engagements (including seeing LTJ Bukem and Bachelors of Science live!), two homework assignments and a midterm to prepare for. On the other hand, once this fortnight is over - life will become a lot easier.
Soon after that, I managed to accidentally smash my bedroom window while fitting my new amplifier and the nights became much cooler. This led to some very chilly nights, which became better when Ryan used his superior duct tape to actually seal the window with cardboard (versus just slotting it in - which was my approach).
Broken glass aside, it's been a monumentally busy month. The day after my last update, I went sea kayaking on the bay with Cal Adventures, the outdoor centre that is run by (affiliated with?) the university. This was a one day introductory course that allows me now to go out on the bay alone (within line of sight of the centre). While the pace of the course was a little slow for my liking, we were extremely lucky to catch such beautiful weather and being out on the bay was a peaceful experience that helped mitigate some of the stress of our second Advanced Robotics assignment.
The calm didn't last for long though because I was soon onto an assignment for Computer Vision. Once this was completed, I had an Advanced Robotics assignment that was due in a week. It had come out late beacuse our Professor had recently changed the questions and had been trying to solve them himself. This took longer than expected...perhaps an ominous sign. Logistics made it impossible to heed his advice that we start immediately and so I tried my best to do it in a week. This proved to be difficult - in the end taking 9 days (using all of my remaining late days).
During those 9 days, I put in about 50 hours of work, getting stuck on the last part of the first question for three days. Despite going to see our teaching assistant three times about it, I got no further. Bad strategy which resulted in me turning in the assignment 70% complete. Whoops. Looks like trying to juggle the job hunt with a graduate degree at Berkeley is a difficult optimisation problem!
This past week has been a bit of a rollercoaster for a number of reasons. After receiving one job offer, the other employers are reacting much more quickly and this next week I have 6 interviews planned. I'm wishing I hadn't scheduled my Google phone screen first - now that I've had numerous telephone screens, I might have screwed that one up much less badly.
A few weeks ago a professor sent around a request for volunteers to pick up/drop author Neal Stephenson from/to the airport. He came to a panel on campus, vaguely entitled 'On The Future: Beyond Computing'. Other members of the panel included Peter Norvig, Director of Research at Google and Jaron Lanier, author and coiner of the term 'virtual reality'. I capitalised on my free Zipcar credit and replied - a few hours after the email was sent around. It looks like my response time was favourable and I was tasked with dropping him off to Oakland airport on the day after the talk. Equally as exciting, Professor Katz invited me to dinner with the panelists afterwards. (Googling Professor Katz revealed him to be one of the creators of RAID. Incredible. I was very tempted to ask him if he knew where my data all went, that one time...)
This was an interesting experience, being both simultaneously over and underwhelming for reasons best explained in person. I'll post a separate note with my takeaways from my conversation with Neal Stephenson. Still, I was buzzing with excitement for a good two days after that. What struck me as most admirable was how normal these tremendously acclaimed people were. I'd always imagined that reaching their heights of 'notoriety' came with some ego inflation but meeting these three demonstrated how untrue that assumption was.
The next day we had the interview at the culmination of our application to Steve Blank's Lean Launchpad class. As I mentioned previously, this was one of the classes that helped me decide to come here and I was quite looking forward to it. The interview itself was short - which indicated that either we had enough information on our application or that they had already made up their mind. We'd put a lot of effort into our application, spending quite a bit of effort researching the space around our proposed 'startup' (similar to my capstone project). They asked questions around our idea and around our team for a total of 5 minutes before we were let free.
A double gin and tonic (or club soda, tonic is expensive here) plus 8.95 hours of sleep later, I woke up to a depressing rejection email from the teaching assistant for the class. We've yet to receive feedback as to our rejection which is strange, because they're normally very quick to queries. The silver lining is that I'll now have significantly more time next semester to sleep, exercise and submit applications for accelerators.
The last couple of days have been moderately alcoholic; after the last few weeks, I was desperate for some mindless social interaction. Yesterday we had our MEng Halloween party and it occurred to me that the primary reason people hold Halloween parties as adults here is to take photos. Despite buying $10 worth of cardboard sheets, some cyan spray paint and duct tape, I ran out of time and wasn't able to recreate a costume based on the Hype Dark robot. One day.
This coming 12 days is going to be the toughest of the semester yet. In addition to the 6 interviews, I have a couple of social engagements (including seeing LTJ Bukem and Bachelors of Science live!), two homework assignments and a midterm to prepare for. On the other hand, once this fortnight is over - life will become a lot easier.
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The tragedy of studying at Cal is that it's a stunningly beautiful place to study but there's scant time to explore! I've been getting slammed the past couple of weeks - having started the many interviews that are to come, and having struggled on a homework assignment. As soon as that was handed in, another was immediately available and I'm back to square one now with two on my plate.
One of the classes I'm taking, Advanced Robotics, is excellent and is exactly what I was looking for in my Master's degree. That said, I can't help feeling somewhat lost with each class. It's getting better as we've moved away from controls (which is ostensibly part of mechanical engineering, which explains why I had no idea what was happening for the first 6 weeks of class) and moved back towards classic AI. It also wasn't immediately clear to me, particularly without a background in controls, what exactly the relevance of the methods we learnt was. I'm now starting to get an appreciation of how you might be able to use them though, mainly through the homeworks.
In the last homework, we programmed a tetris game AI that uses an approximate linear program to generate a policy for how best to play tetris. We also applied linear quadratic regulators to help stabilise a inverted pendulum (a famous problem, also known as the cartpole problem) and to hover a helicopter. In the first case, we used a convex optimisation library called CVX to solve a linear problem. This approach seems particularly common in courses here at Berkeley.
I helped my teammate Gita out with one his homework assignments to find the shortest path in a graph. Instead of just asking students in his class (CE290i) to implement Dijkstra's, they managed to shoehorn the most horrific Java wrapper of a C linear program solving library into their assignment. Instead of writing a beautiful piece of code that could have solved the shortest path problem in maybe ~ 20 lines of Java code at a stretch, it was necessary to generate a string, pass it via some obfuscated interface to this solver and parse the output (of questionable precision). Yuck.
For the majority of my assignments I've been using MatLab, which presents a nice clear interface for implementing programmatic solutions to mathematical problems. It's not my favourite language though - I like writing clean code and it's easily possible to write unintelligible code in MatLab. Perhaps in the same way that you could in other weakly typed languages like Python or Javascript. MatLab also runs extremely slowly - being an interpreted language. Prof Abbeel mentioned that if you were actually implementing these solutions, you'd use C and see a speedup of ~ 1000 times.
In particular, one of the ideas that came to me during the many bleary eyed hours I spent staring at / trying to do the second homework was to use some of the control policy algorithms from robotics to control thyroid disease. As I've mentioned before - I suffer from Hashimoto's thyroiditis, an autoimmune disorder which effectively means my thyroid gland functions less well over time. The typical approach advocated by mainstream physicians treats it pretty poorly. I feel normally energetic on about 1 in 7 days. The other 6 days of the week I'm sleepy for a good part of the day (hypothyroid). Often I'm unable to focus well (hyperthyroid). It's a difficult condition to live with as a normally productive person. Still, I manage.
Where a control algorithm could come in is by more closely modelling the relationship between the different thyroid 'variables'. The normal treatment assumes that a patient's TSH (thyroid stimulating hormone) level is inversely proportional to their Free T4 (thyroxine) level. i.e., if your TSH is high, you need more synthetic thyroxine. If it is low, you need less. From my reading and shallow understanding of the endocrinological system, that's not an accurate assessment of the situation. There are perhaps five variables, if not more that need to be tracked. A patient's thyroid gland may not adequately convert T4 into T3 (this is the form of thyroxine that is usable by the body). Additionally, this conversion takes its toll on their adrenal system, requiring cortisol to carry out the conversion (I think). Taking supplemental T4 for a significant period of time can deplete these levels.
I'd be interested in trying to work out the actual relationship between these variables and perhaps implementing a control algorithm that could determine the optimal policy for medicating a patient. The only caveat is that collecting this data would be exorbitantly expensive (~ $200 for every data point) and that you'd need a lot of it. This is one of those projects that might have to wait for my one-day startup to go public. Incidentally, this autoimmune disorder is the same that Larry Page suffers from. I'm hoping that having a billionnaire with the same problem means some actual research will be done into it :).
This digression aside, these assignments are tough. I suspect they'd be easier if it hadn't been 4 years since I finished my undergraduate degree (and about 6 years since I last studied any maths). The Advanced Robotics course is tough too because I'm the only Master's student taking the course. I've tried to make friends with PhD students to study with but it's difficult - they have their own offices and are generally smarter than me! Luckily there is a sizeable group of Master's students to work on Computer Vision assignments with and that seems to be going well so far.
The other main activity of the last two weeks has been forming (by way of recruiting MBA students) a team for our application to the Lean Launchpad class at the Haas (business school) run by Steve Blank. This is one of the classes that helped me choose to attend Cal based on the advice of Kevin Yien and a handful of other students. This started with almost getting shot down by Steve Blank after my very first pitch at the information session (thankfully saved by an accurate but witty retort). It continued with a networking session and ended up with us forming a team with three MBA students, myself and my teammate Gita - also an engineering student.
Somehow this class wasn't widely advertised amongst CS graduate students and most MBA students wanted people who could build software for their teams. It was a little sad to take myself off the market of available team members. This class won't fulfil my core requirements next semester which means I'll be taking it in additional to my normal workload. I'm hopeful that there is some crossover between the work in the class and our capstone project. Still, next semester is going to be extremely busy.
I've made a conscious effort this week not to buy granola. That was my comfort food of choice and being high in both sugar and fat, it probably wasn't doing good things for my health in the quantity that I was consuming it. I've also succumbed to the coffee shop culture here and have been consuming caffeine regularly. Hopefully I'll get a chance to reset soon.
One of the classes I'm taking, Advanced Robotics, is excellent and is exactly what I was looking for in my Master's degree. That said, I can't help feeling somewhat lost with each class. It's getting better as we've moved away from controls (which is ostensibly part of mechanical engineering, which explains why I had no idea what was happening for the first 6 weeks of class) and moved back towards classic AI. It also wasn't immediately clear to me, particularly without a background in controls, what exactly the relevance of the methods we learnt was. I'm now starting to get an appreciation of how you might be able to use them though, mainly through the homeworks.
In the last homework, we programmed a tetris game AI that uses an approximate linear program to generate a policy for how best to play tetris. We also applied linear quadratic regulators to help stabilise a inverted pendulum (a famous problem, also known as the cartpole problem) and to hover a helicopter. In the first case, we used a convex optimisation library called CVX to solve a linear problem. This approach seems particularly common in courses here at Berkeley.
I helped my teammate Gita out with one his homework assignments to find the shortest path in a graph. Instead of just asking students in his class (CE290i) to implement Dijkstra's, they managed to shoehorn the most horrific Java wrapper of a C linear program solving library into their assignment. Instead of writing a beautiful piece of code that could have solved the shortest path problem in maybe ~ 20 lines of Java code at a stretch, it was necessary to generate a string, pass it via some obfuscated interface to this solver and parse the output (of questionable precision). Yuck.
For the majority of my assignments I've been using MatLab, which presents a nice clear interface for implementing programmatic solutions to mathematical problems. It's not my favourite language though - I like writing clean code and it's easily possible to write unintelligible code in MatLab. Perhaps in the same way that you could in other weakly typed languages like Python or Javascript. MatLab also runs extremely slowly - being an interpreted language. Prof Abbeel mentioned that if you were actually implementing these solutions, you'd use C and see a speedup of ~ 1000 times.
In particular, one of the ideas that came to me during the many bleary eyed hours I spent staring at / trying to do the second homework was to use some of the control policy algorithms from robotics to control thyroid disease. As I've mentioned before - I suffer from Hashimoto's thyroiditis, an autoimmune disorder which effectively means my thyroid gland functions less well over time. The typical approach advocated by mainstream physicians treats it pretty poorly. I feel normally energetic on about 1 in 7 days. The other 6 days of the week I'm sleepy for a good part of the day (hypothyroid). Often I'm unable to focus well (hyperthyroid). It's a difficult condition to live with as a normally productive person. Still, I manage.
Where a control algorithm could come in is by more closely modelling the relationship between the different thyroid 'variables'. The normal treatment assumes that a patient's TSH (thyroid stimulating hormone) level is inversely proportional to their Free T4 (thyroxine) level. i.e., if your TSH is high, you need more synthetic thyroxine. If it is low, you need less. From my reading and shallow understanding of the endocrinological system, that's not an accurate assessment of the situation. There are perhaps five variables, if not more that need to be tracked. A patient's thyroid gland may not adequately convert T4 into T3 (this is the form of thyroxine that is usable by the body). Additionally, this conversion takes its toll on their adrenal system, requiring cortisol to carry out the conversion (I think). Taking supplemental T4 for a significant period of time can deplete these levels.
I'd be interested in trying to work out the actual relationship between these variables and perhaps implementing a control algorithm that could determine the optimal policy for medicating a patient. The only caveat is that collecting this data would be exorbitantly expensive (~ $200 for every data point) and that you'd need a lot of it. This is one of those projects that might have to wait for my one-day startup to go public. Incidentally, this autoimmune disorder is the same that Larry Page suffers from. I'm hoping that having a billionnaire with the same problem means some actual research will be done into it :).
This digression aside, these assignments are tough. I suspect they'd be easier if it hadn't been 4 years since I finished my undergraduate degree (and about 6 years since I last studied any maths). The Advanced Robotics course is tough too because I'm the only Master's student taking the course. I've tried to make friends with PhD students to study with but it's difficult - they have their own offices and are generally smarter than me! Luckily there is a sizeable group of Master's students to work on Computer Vision assignments with and that seems to be going well so far.
The other main activity of the last two weeks has been forming (by way of recruiting MBA students) a team for our application to the Lean Launchpad class at the Haas (business school) run by Steve Blank. This is one of the classes that helped me choose to attend Cal based on the advice of Kevin Yien and a handful of other students. This started with almost getting shot down by Steve Blank after my very first pitch at the information session (thankfully saved by an accurate but witty retort). It continued with a networking session and ended up with us forming a team with three MBA students, myself and my teammate Gita - also an engineering student.
Somehow this class wasn't widely advertised amongst CS graduate students and most MBA students wanted people who could build software for their teams. It was a little sad to take myself off the market of available team members. This class won't fulfil my core requirements next semester which means I'll be taking it in additional to my normal workload. I'm hopeful that there is some crossover between the work in the class and our capstone project. Still, next semester is going to be extremely busy.
I've made a conscious effort this week not to buy granola. That was my comfort food of choice and being high in both sugar and fat, it probably wasn't doing good things for my health in the quantity that I was consuming it. I've also succumbed to the coffee shop culture here and have been consuming caffeine regularly. Hopefully I'll get a chance to reset soon.
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This week marked the beginning of the Fall recruitment cycle on campus where hundreds of employers will try their best to attract Cal students. That's actually a little incorrect - employers don't seem to have try very hard here, certainly not as hard as employers tried during my time at Cambridge. I'll go into more detail about that later.
As you can imagine, engineering jobs are very prevalent here - certainly disproportionately so, compared to most other types of jobs. In particular, software engineers were sought after by nearly every firm, which has made my job easier. This past week we had the university wide careers fair, which showcased a few hundred employers and was spread over three days. On Wednesday this coming week is the EECS (Electronic Engineering and Computer Science) career fair, which I'm very much looking forward to. In a few weeks time is the Startup Fair, which should be equally exciting.
We also had an Employers' Breakfast before the second day of the career fair this last week. This was interesting but it seems as if the employers hadn't been fully briefed on who was attending this breakfast. For instance, one recruiter was looking for software engineers graduating in December to begin work in January. She didn't realise that every single person in the room was on the MEng program which finishes in May. Whoops.
My attitude towards the job hunt here has been somewhat cavalier. I acknowledge that as a software engineer, it's not going to be difficult to get, at the very least, interviews at the firms I want to work at. (Whether I make it through each firm's gauntlet of interviews is another question entirely...) Having had five internships now and three years of experience, it's fair to say that I have an understanding of what kind of work I'd like to do and for what sort of company. A lot of the companies presenting at the fair were the usual big corporates which were not particularly exciting. A lot of the companies also refused to sponsor international students - which is an issue I've never encountered before back home (being a British citizen).
Using all four of these metrics, I was able to make my 'walk' of the fair more efficient. (I also looked up the list of employers online and filtered them down beforehand, so I knew exactly which stalls to go each day.) This seemed less arduous than what many undergrads and many of my less selective MEng colleagues were doing - visiting each stall in turn. Given the extensive queues at each stall, it looked like a painfully slow process. (Tip for future fairs: get there at the beginning. At 11am it was basically empty. At 12pm it was BUSY.)
I've been a little confused by how the process works here, having read that employers receive thousands of online applications and you're best served by putting your resume directly in front of them. Before I came to Berkeley, I made an extensive spreadsheet detailing the exact jobs at employers I'd want to work for but held off applying directly until I could meet the recruiters directly because of this advice. As it turns out, there's no right answer - it depends on how meticulous (or disorganised) the recuiter is.
The process here essentially works as follows (note that I omitted many of these steps):
1) Dress unlike you normally dress. Dress unlike you would normally dress at work. Wear your smartest suit. (Seriously?)
2) Bring a portfolio of resumes. Preferably customised for each employer but if you don't have time, it's fine to bring multiple copies of the same resume, as long as you customise the 'objective' statement on your resume. (I didn't have space for an 'objective' on my 1 page resume. I wrote individual cover letters for my shortlist of firms.)
3) Queue at your stall and prepare to overhead many conversations where students try to sell themselves to the recruiter. (Queueing, ugh.)
4) Introduce yourself to the recruiter. Hand them your resume.
5) Ask them specific questions about their job while they scan your resume. Try to sell yourself through these questions. (I think my questions were possibly a little too efficient.)
6) Try not to appear unnerved while they make marks on your resume. (As long as it's not a big X you're hopefully OK.)
7) Go home and submit another resume online. Turns out the one you gave them was just for them to later more easily retrieve your online application. (Apologies to the trees out there.)
This whole process seems so completely over the top to me, especially coming from a university like Cambridge where the balance of power between employers and students was the other way. Firstly, wearing a suit to a careers fair? If any employer is so crass as to judge candidates by their appearance even BEFORE their interview, then I'd have serious questions about their work culture! As for queueing up to be pre-screened at the careers fair, it all seems rather backwards to me. The reason we have online applications is that it's all the more efficient. To fall back to paper because of the volume of applicants is just crazy but seemingly necessary.
The only justification I can come up with is that Cal is a BIG university with a lot of students. Getting any sort of job here is a tougher process than back at Cambridge. There are applicants from all over the US from many other equivalently good universities and employers can be as selective as they like. In England, Oxford and Cambridge are, for some reason, in a league of their own above other universities. There are also just 70-90 computer science undergraduates coming out of Cambridge each year. It's easy to see why they're so much more in demand. Here on the other hand, several thousand undergraduates roll out of Cal and other similarly prestigious universities every year. Every competitive advantage helps.
As you can imagine, engineering jobs are very prevalent here - certainly disproportionately so, compared to most other types of jobs. In particular, software engineers were sought after by nearly every firm, which has made my job easier. This past week we had the university wide careers fair, which showcased a few hundred employers and was spread over three days. On Wednesday this coming week is the EECS (Electronic Engineering and Computer Science) career fair, which I'm very much looking forward to. In a few weeks time is the Startup Fair, which should be equally exciting.
We also had an Employers' Breakfast before the second day of the career fair this last week. This was interesting but it seems as if the employers hadn't been fully briefed on who was attending this breakfast. For instance, one recruiter was looking for software engineers graduating in December to begin work in January. She didn't realise that every single person in the room was on the MEng program which finishes in May. Whoops.
My attitude towards the job hunt here has been somewhat cavalier. I acknowledge that as a software engineer, it's not going to be difficult to get, at the very least, interviews at the firms I want to work at. (Whether I make it through each firm's gauntlet of interviews is another question entirely...) Having had five internships now and three years of experience, it's fair to say that I have an understanding of what kind of work I'd like to do and for what sort of company. A lot of the companies presenting at the fair were the usual big corporates which were not particularly exciting. A lot of the companies also refused to sponsor international students - which is an issue I've never encountered before back home (being a British citizen).
Using all four of these metrics, I was able to make my 'walk' of the fair more efficient. (I also looked up the list of employers online and filtered them down beforehand, so I knew exactly which stalls to go each day.) This seemed less arduous than what many undergrads and many of my less selective MEng colleagues were doing - visiting each stall in turn. Given the extensive queues at each stall, it looked like a painfully slow process. (Tip for future fairs: get there at the beginning. At 11am it was basically empty. At 12pm it was BUSY.)
I've been a little confused by how the process works here, having read that employers receive thousands of online applications and you're best served by putting your resume directly in front of them. Before I came to Berkeley, I made an extensive spreadsheet detailing the exact jobs at employers I'd want to work for but held off applying directly until I could meet the recruiters directly because of this advice. As it turns out, there's no right answer - it depends on how meticulous (or disorganised) the recuiter is.
The process here essentially works as follows (note that I omitted many of these steps):
1) Dress unlike you normally dress. Dress unlike you would normally dress at work. Wear your smartest suit. (Seriously?)
2) Bring a portfolio of resumes. Preferably customised for each employer but if you don't have time, it's fine to bring multiple copies of the same resume, as long as you customise the 'objective' statement on your resume. (I didn't have space for an 'objective' on my 1 page resume. I wrote individual cover letters for my shortlist of firms.)
3) Queue at your stall and prepare to overhead many conversations where students try to sell themselves to the recruiter. (Queueing, ugh.)
4) Introduce yourself to the recruiter. Hand them your resume.
5) Ask them specific questions about their job while they scan your resume. Try to sell yourself through these questions. (I think my questions were possibly a little too efficient.)
6) Try not to appear unnerved while they make marks on your resume. (As long as it's not a big X you're hopefully OK.)
7) Go home and submit another resume online. Turns out the one you gave them was just for them to later more easily retrieve your online application. (Apologies to the trees out there.)
This whole process seems so completely over the top to me, especially coming from a university like Cambridge where the balance of power between employers and students was the other way. Firstly, wearing a suit to a careers fair? If any employer is so crass as to judge candidates by their appearance even BEFORE their interview, then I'd have serious questions about their work culture! As for queueing up to be pre-screened at the careers fair, it all seems rather backwards to me. The reason we have online applications is that it's all the more efficient. To fall back to paper because of the volume of applicants is just crazy but seemingly necessary.
The only justification I can come up with is that Cal is a BIG university with a lot of students. Getting any sort of job here is a tougher process than back at Cambridge. There are applicants from all over the US from many other equivalently good universities and employers can be as selective as they like. In England, Oxford and Cambridge are, for some reason, in a league of their own above other universities. There are also just 70-90 computer science undergraduates coming out of Cambridge each year. It's easy to see why they're so much more in demand. Here on the other hand, several thousand undergraduates roll out of Cal and other similarly prestigious universities every year. Every competitive advantage helps.
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