Like learning math, bio, econ, etc but worried how fast you forget? We are offering a PhD position to fix that with ML algorithms, FOSS software, and cognitive testing at the Cluster of Excellence Machine Learning for Science at the University of Tübingen. The position is joint between our group (the ML ⇌ Science Colaboratory) and the Human and Machine Cognition Lab. We are very pro-Julia.
For details, see the posting.
Application deadline approaching October 15th! If you have questions about this exciting position, please feel free to contact us!
Hello, thanks for posting. A E13 TV-L 65% position refers to a 26h/week of workload, is that right? So I suppose it admits a parallel part-time job, correct? If not, please make me know. Thanks in advance for your attention. Kind regards.
So tempting and interesting! I thought I would suggest to make part of the study how pacing reviews affects the ability of the student to solve novel problems.
I mention because my feeling is that students that rely on their long term memory to solve problems might develop different skills than those that don’t making the former more competent than the latter but less creative.
Hi Rodrigo, you are right about the formal hours. The origin of “fractional PhD positions” (I myself had a 50%) in Germany is that one got paid for teaching (e.g. 19h/week) and did the PhD on the side.
The reality of it is that in most STEM fields the candidate puts 100% or more of her/his time on the PhD, because the research is demanding and the fields are competitive (or the topic is absorbing, and that is all you want to do ;)).
If you are a demonstrably productive person that can meet the publication requirements of a PhD in ML while having a second job, this is worth trying and I encourage you to apply. A positive aspect of this position is that there are no teaching obligations (but we can find you teaching if you want to grow in this area).
Kind regards, and feel free to write to me for further questions, Álvaro.