ML ⇌ Science Colaboratory | Eberhard Karls Universität Tübingen | Researcher in scientific ML | Onsite in Tübingen, Germany | https://www.mlcolab.org/ The Machine Learning ⇌ Science Colaboratory from the Eberhard Karls Universität Tübingen is looking for a motivated, skilled researcher working at the intersection of science, engineering, and people.

About us

We want to raise the power of scientific discovery by thoughtful application of machine learning techniques — closely working together with the research community of the University of Tübingen spanning the natural sciences, the social sciences, and the humanities.

Your role

    • You will collaborate with scientists and ML researchers, teach practical ML, and write fast, reproducible, and documented code. 
    • You will be contributing your experience toward developing models and software, coaching and giving advice, designing compelling explanations, and delivering them to postgraduate audiences. 
    • You will interact with scientists and ML researchers to set up joint projects, sometimes leading teams to carry them out. 
    • Our group is collegial and collaborative with access to exciting datasets and ML expertise in our research network that facilitate formulating projects aligned with our mission and your interests. Involvement in peer-reviewed publications is welcome but not required.
    • The position is E13  TV-L 100% in the salary scale, initially until end of 2025. You can check the range of the salary in the calculator linked, but if you have any questions, don't hesitate to contact us at mlcolab@inf.uni-tuebingen.de
 (Link for salary calculator: https://oeffentlicher-dienst.info/c/t/rechner/tv-l/west?id=tv-l-2023)

Your profile You possess a PhD degree in a quantitative discipline, good programming and teaching skills, and hands-on experience training deep learning ML models. How to apply

To apply, send your application (including cover letter, CV, transcript of records, links to code) in one single pdf file to Emily Gabaldón <emily.gabaldon@uni-tuebingen.de> by 2.04.2023.

Find more information about us online in https://mlcolab.org/

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