308 karma · joined May 25, 2012
Previously Materials Science and Engineering postdoc at HU Berlin, PhD at Cal.
https://zeissgroup.wd3.myworkdayjobs.com/External/job/Jena/S...
https://zeissgroup.wd3.myworkdayjobs.com/External/job/Jena/Q...
https://zeissgroup.wd3.myworkdayjobs.com/External/job/Jena/H...
https://zeissgroup.wd3.myworkdayjobs.com/External/job/Jena/P...
https://zeissgroup.wd3.myworkdayjobs.com/External/job/Jena/S...
https://zeissgroup.wd3.myworkdayjobs.com/External/job/Jena/S...
https://zeissgroup.wd3.myworkdayjobs.com/External/job/Jena/S...
Zeiss SMT is the leader in extreme engineering optics for semiconductor manufacturing. We come up every so often on HN as leaders in EUV optics manufacturing for ASML scanners. SMS is a branch of SMT concerned with standalone tooling for quality assurance and defect inspection in semiconductor fabs (tools like the AIMS EUV or PROVE systems, for example). We bring complete solutions to the hypercompetitive market that is the semiconductor industry. The scale is vast – the work you can be involved in ranges from simulations at the nanometer to how to ship tools via using Boeing 747(s).
Software (and extremely diligent/precise engineering… honestly it blows my mind regularly) underpins everything we do and spans the same vastness of scale. We (Zeiss SMT, but also SMS where I work) are hiring in pretty much every IT field as we modernize systems, upgrade legacy code, and build cutting-edge new tools and platforms to remain at the front of the field. Specifically interesting to HN (I think) is my team, which works on developing extremely fast physics simulation and data processing code utilizing classical algorithms, machine learning, and _AI_, all on premise. We also build and maintain the hardware (HPC clusters) to enable these developments.
Desirable skills Python (scientific, HPC, ML, physics simulation), image analysis (big, big data processing, very fast), CUDA, C++, HPC architecture design/on premise rack configuration, HPC admin, DevOps infrastructure (physical as well as CI/CD), GPGPU programming, FPGA programming, QA engineering, Kubernetes
I can post some job links tomorrow, but if you have questions please either comment or reach out to me at thomas dot pekin at zeiss dot com. I’ve been working here for a year and it’s a lot of fun.
=== START OF SMART DATA SECTION ===
SMART overall-health self-assessment test result: PASSED
SMART/Health Information (NVMe Log 0x02)
Critical Warning: 0x00
Temperature: 35 Celsius
Available Spare: 100%
Available Spare Threshold: 99%
Percentage Used: 4%
Data Units Read: 268,644,677 [137 TB]
Data Units Written: 259,969,878 [133 TB]
Host Read Commands: 1,213,441,896
Host Write Commands: 981,264,397
Controller Busy Time: 0
Power Cycles: 125
Power On Hours: 793
Unsafe Shutdowns: 7
Media and Data Integrity Errors: 0
Error Information Log Entries: 0
Read 1 entries from Error Information Log failed: GetLogPage failed: system=0x38, sub=0x0, code=745One of the main differences for me is that the .py file is run in its entirety (outside of if/else blocks for loading data). That usually corresponds to multiple cells of a Jupyter notebook that one would need to Ctrl+Enter through, where missing one would cause a problem.
The second is just how you can decouple the code and the terminal - it's a personal pet peeve that Jupyter notebooks jump around when running through cells - I don't want to be scrolling all around just to reset some variables to their original values, and it's really nice to run a whole .py script and see an output side by side, where the script is much longer than my screen. I can keep it open at the important part in VSCode, and change some intermediate process, and let all of the ad hoc plotting code remain at the bottom.
Finally, the biggest difference for me is how figures behave - the way I have it set up is that they open in their own window and remain interactive (can zoom/pan). I know you can do it in Jupyter as well, but the workflow really emphasizes inline plotting with non-interactive plots, especially when it comes to sharing them. But with the .py script and IPython command line, I can open up 5 figures, tile them however I'd like, and then refer to them by name/number in my script, so I can clear and overwrite them however I'd like, and they don't close or move around. This makes comparing things very easy, like how changing a parameter changes the rest of my analysis.
Lastly - the way it is set up is more like Matlab... whoops, but I think their workflow is much more ergonomic than a notebook. However, for sharing with other people, I usually just copy and paste the various parts of my scripts into a notebook, as that is the de facto standard.
https://www.phonearena.com/news/Google-Photos-High-quality-v...
From
if (x > y) {
do_something();
} else {
do_something_else();
}
to the form if (x <= y) {
do_something_else();
} else {
do_something();
}
What happens when x or y are NaN?Water molecules are molecules, and therefore have a more complex electronic structure than atoms, and therefore is harder to describe, especially at the extremes.
https://faq.whatsapp.com/general/download-and-installation/a...
https://en.wikipedia.org/wiki/Convolution#Fast_convolution_a...