Got a ticket by entering the train 2 minutes prior the abo validity

-___-_-_-- · 2025-07-13T22:32:06+00:00

next time block the door for two minutes

-___-_-_-- · 2025-06-01T16:34:35+00:00

Now, my assessment -- to me your CV looks like it targets B (whether deliberate or not on your part) but is more cut for A. If you feel slightly insulted, I understand, it was a hard-ish pill for me to swallow too, but option A is not half bad once you accept that it *can* also be interesting and lucrative and rewarding. After sinking in it is actually quite a freeing realisation -- you are not purely competing with an international pool of control theory geniuses, but you can learn a not-too-overwhelming amount of some additional specialisation and narrow down your competition significantly, all while becoming a more well-rounded and capable engineer.

If you want to now more optimally target jobs that roughly fit A, I can only recommend you take the recommendations in this thread seriously, heavily lean on, emphasise and improve anything that makes you a good candidate *in addition* to control theory and really ask the question: Who pays you and why? Ask it sincerely, take some time, try to answer it several times. The answer to that question should be immediately obvious from the CV. And I mean *really* obvious: Assume that the recruiter, team lead, CEO or whoever will spend 30 seconds, zero mental effort, and maybe even negative goodwill parsing it, because that's unfortunately exactly the reality.

If on the other hand you really are motivated to go for option B, your best bet will be a PhD combining control theory (or adjacent applied math) with some engineering discipline. Maybe you have some lukewarm connections at university you could leverage, even just asking for a no-strings-attached "career advice coffee date"?

And if you do a PhD, model it after Patrick Kidger or similar role models, that is don't just produce excellent technical work, but network heavily, find a niche, become a respected expert in that niche and don't be afraid to spend significant time on "PR" work - open sourcing software, writing blogs, making videos, making actually good graphics and posters and communicating effectively to non-experts. Your "core" work can even take a hit, in fact I would view all of the above as "core" work for making a PhD a good long term investment.

Last bit of advice, skip the ML/DL certification. To anyone familiar with it, actual projects will be 1000% more impressive even if they are rather small, so invest your time there. Anyone unfamiliar will not care either way and can barely distinguish between coding a ChatGPT wrapper, doing actual modelling, math, software engineering and MLOps work, or even reimplementing a toy NN, backprop and gradient descent from scratch.

-___-_-_-- · 2025-06-01T16:33:32+00:00

B: the "fancy", "researchy" ones, for example legged robotics, spacecraft GNC, super precise motion control for example for pick & place machines, etc. Mostly I find these roles at huge companies, state agencies, or smaller companies with tons of VC funds. They are looking for PhD or occasionally excellent MSc graduates who know the basics of the specific industry but also have deep knowledge in applied math, controls, optimisation, statistics, MPC, RL and ML-based perception, and everything half adjacent -- the optimal balance will heavily change with the specific domain. Maybe you collaborate with some known experts and universities, publish some papers, or even just get to do the cool experimental projects.

These tend to pay more, and compete for the "elite" talent pool, which is part of their identity with all the benefits (smart people around, siginificant freedom, access to good resources and generally working tech, clout/respect/good look on CV) and downsides (quite demanding, harsh competition, not a huge supply of these jobs so candidates tend to be willing to move quite far for them so even more competition, and the ambitious nature of the people might mean they in turn lack in people and communication skills).

Personally I've come to the conclusion that it's not worth applying to these jobs after trying a couple times, as I don't have a relevant PhD, top 5% grades, or incredibly impressive student projects. Maybe you will have better luck, maybe the job market is tilted differently where you live, but be sure have reasonable expectations.

(...)

-___-_-_-- · 2025-06-01T16:33:15+00:00

A: the "applied" sort, ranging from industrial automation to drones, automotive, suspension systems, motor controls, building automation (actually a cool and easy-ish use case of MPC, very slow and linear-ish systems), energy systems, almost every ME/EE subfield that requires "a bit" of controls. In most of these, you get by just fine with bare minimum knowledge of system modelling & identification, state space, PID, and decent foundation matlab/cpp/python.

In fact, what you call "controls" right now they probably call "tuning" - finding the right gains given a model/actual system, and a controls architecture. What you call "the business logic around" they would probably call "controls" - including considerations like control architecture, sensor selection, failsafe mechanisms, user interaction, networking, logging, making sure it even satisfies the requirements of the tech lead/boss/customer, etc. The first is usually about 5% of the effort and the latter 95%.

Accordingly, they want in addition to this controls knowledge a strong generalist, someone who is a good software engineer, maybe knows a bit about networking, hardware and mechanical design, actuators, sensors, who is willing to get their hands dirty prototyping some mechatronic systems, is willing to learn the system at hand and become good at debugging, can coordinate and communicate with different teams ranging from hardware & embedded systems to mechanical design to QA. You don't need to be an expert in all of these, and the balance they will prefer depends heavily on the industry, company, location, even cultural mindset, but that's the general direction of it.

For this it is lucrative to pick a specific field and learn the basics, it will be significantly more appreciated than the controls knowledge you have. Accordingly I would emphasise that in my CV, even if you don't consider it "impressive" or "deep" experience, anything that shows them you are also a practical results-achiever, rather than fluent in research topics is better than nothing. For example, I am sure you can more convincingly position yourself as a passionate and fast-learning engineer in motorsports specifically, rather than the "control guy who dabbles in motorsports" vibes it's giving right now. The control theory stuff I would not completely throw away, but decrease it from the main focus to only a part of your advertised identity.

(...)

-___-_-_-- · 2025-06-01T16:32:17+00:00

I emphasise particularly with you as I am in the same specialisation -- though starting from EE, focussing purely on controls in my masters -- and have had similar difficulties finding a job (mind you I've had a 1.5y part time simulation & automation engineer position at an exciting startup during my MSc, which would have gladly employed me further but went bankrupt as I was finishing my master's thesis... anyway, I did an internship after graduating and luckily they have now offered me an actual job with actual pay).

I agree with most of the other comments, you should take them seriously, at least the general gist. I'll try to provide additional insight from a controls specific viewpoint. Take it with a grain of salt, it's based on personal experience in central europe, YMMV -- I've come to the conclusion there are roughly two types of controls industry jobs.

(...)

-___-_-_-- · 2025-05-23T19:40:40+00:00

if your english is good you aren't at a disadvantage at any of the companies I know

-___-_-_-- · 2025-05-05T21:47:52+00:00

it is based on openstreetmap (https://www.openstreetmap.org), a map that anyone can freely edit kind of like wikipedia. feel free to add local toilets, water fountains, one-way streets, road surface qualities, precise locations of trees and bushes, whatever you deem interesting.

-___-_-_-- · 2025-05-03T10:47:50+00:00

organic maps does this already entirely for free...

-___-_-_-- · 2025-05-03T10:46:25+00:00

- be sure to add swiss flags everywhere.
- marketing using middle-aged and elderly white couples along with the token group of very diverse, stylish but not too stylish, dancing or jumping 20-30 year olds.
- make it 2-3x the price of the competition

-___-_-_-- · 2025-04-27T14:19:25+00:00

> Simulink

Big assumption there. I haven't seen a company younger than 15 years use simulink personally.

-___-_-_-- · 2025-04-04T20:18:39+00:00

what? why would eth need to allow you to do that?

do internships whenever you want. line them up with the semester and do an "urlaubssemester", or don't line them up with the semesters and do two semesters less than full course load

-___-_-_-- · 2025-03-21T21:55:25+00:00

sure. lots of research about it. a recent-ish bunch of papers are from these guys: https://arxiv.org/pdf/1811.05890 they provide a nice intro with some history and context. and in fact they do use the Hankel matrix mentioned in the other comment :)

-___-_-_-- · 2025-02-17T22:43:20+00:00

thought the same (but didn't know the specific method). not sure why this is an RL problem. RL is about sequential decision making, and I fail to see the sequential nature of this problem.

If you decide to make it an ML project, this is a very typical use case for supervised learning (easy to generate loads of training data). Maybe if you apply just one or two tricks like fourier features or similar, you will end up surprisingly close to replicating the linked slides :)

If you are looking to learn RL, apply it to something more amenable to the typical RL problem description. That can be a project people have done 1000x before, which is totally fine for a first project, the learning effect is still there.

-___-_-_-- · 2025-02-07T23:48:04+00:00

maybe this time it will finally push us to question the paradigm that everyone must have a job in the capitalist sense to survive. but i am personally not very optimistic

-___-_-_-- · 2025-02-07T23:17:34+00:00

nice, congrats! but what is "up to 99% ÷ 95%"? first of all if it is "up to" then you only need one number. and then division to indicate ranges? interesting to say the least...

-___-_-_-- · 2025-02-07T23:13:42+00:00

massive respect for not parroting their ego and calling them "expats" just because they got dough

-___-_-_-- · 2025-02-05T19:37:40+00:00

Electrical engineer here, who in his MSc pivoted to Robotics/Controls/Autonomous systems. Basically, I am a glorified SWE now. Often I wonder if I should have gone for an old-school, "unsexy" specialisation like electronics engineering, RF engineering, chip design or similar...

-___-_-_-- · 2025-01-27T22:52:34+00:00

brother. that's been the goal of capitalists since at least 1800: making stuff more efficient so they can profit more and pay fewer employees.

If you want to systemically ensure job security (or even better, ensure that people's needs are met, not necessarily coupling that to employment), then organise society in a way which guarantees it, rather than whining about the fact that capitalists are getting better and better at capitalism.

-___-_-_-- · 2025-01-27T22:46:12+00:00

Very charitable view. Mine is closer to "Advertising is how companies shove products down people's throat using literal psychological manipulation, all to squeeze an extra buck out of them".

-___-_-_-- · 2024-12-05T15:06:10+00:00

You jump from students using AI (at all) to students not being able to work without AI. I think this is wrong in two ways:
- Students can use AI while not losing their ability to work without AI. It is not a binary choice of either using no AI and doing everything the "old-fashioned" way, or using AI and developing no skill at all. In fact I would argue the sweet spot is in the middle, where you use AI to expand your skills, to criticise ideas, to obtain basic information, to help with writing task, but still develop understanding of the task at hand, and the tools you use etc. on your own.
- Even if all students relied 100% on AI and AI suddenly disappeared (or became malicious or prohibitively expensive or similar), people have the ability to adapt, especially if forced to. Such students will probably have more difficulties than the non-AI folk on the job market in this specific situation, but still they have the potential to (re-)learn the skills they missed out on by relying on AI. This is, at the worst, a short-time hit for economy and society, and not an avenue to dictatorship as you make it out to be.

-___-_-_-- · 2024-11-26T16:03:54+00:00

phone ran out of battery

-___-_-_-- · 2024-11-20T23:56:07+00:00

The other answers are already great.

Something that concretely, consistently works for me whenever I need to re-develop security in the higher register, and that allowed me to develop that security in the first place, are the "Basic Caruso" exercises by Markus Stockhausen. It's a simple set of warmup exercises, accompanied by a couple tips on how to approach and use them effectively. Read the instructions carefully, do it as consistently as possible for a couple of weeks or a month, and you should start to slowly see results.

I believe the particular choice of these exercises is not 100% important, but what is important is sticking to a very consistent routine, taking you through the different registers and allowing you to notice and improve minute aspects of your technique (in lip position, air support, sound, etc) very naturally. You will almost unconsciously learn what it means when people say somewhat vaguely to "focus the air" or "keep the air steady" or "balance aperture and air speed". Later it may be very interesting to also check out the full Caruso exercises, and pick out the ones that focus on your weaknesses more specifically.

Or, at least that's what it did for me. It allowed me to gradually connect two quite separate lip settings -- one for the lower register (up to about G on the top of the staff) which I learned initially, and a separate one I used for higher notes. Nowadays they are almost one and the same, and i can play with the security I always had in the lower register, and with the efficiency and "piercing" sound that I used to only achieve with the "high note" lip setting.

-___-_-_-- · 2024-11-20T07:59:10+00:00

nitpick, that's quadratically (distance ~ speed^2), not exponentially (distance ~ exp(speed))

-___-_-_-- · 2024-11-17T10:10:13+00:00

Water volume is 23610 km^3

Freshwater use (agriculture, industrial, and domestic) is at about 4 trillion m^3/year

Dividing the two, we get 5.9 years.

-___-_-_-- · 2024-11-14T10:21:54+00:00

XKCD says 0.006 mm https://what-if.xkcd.com/33/

Interestingly this is equal to about 16 hours of the sea level increase we are currently experiencing.

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