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Nov 23, 2022 12:35 PM
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Strengthening data skills of early career scientists
This call is an opportunity for a tight collaboration between data science and domain science, over three years. Together, we would advance the use of data-driven analysis and ML in your field by carrying out an innovative project, with previously underutilized techniques.
To get started, drop an e-mail to Álvaro, at alvaro.tejero@uni-tuebingen.de.
Key points of the call
Selected goals
- Broaden and deepen the data literacy of early career scientists by collaboration with a data partner.
- Advance disciplines where recent ML methods have not yet been exploited for discovery.
Formal aspects
- 💲Funding corresponds to about two positions (PhD, Postdoc, Junior Group Leader) for 36 months — we envisage one with us and one you / with you.
- 📚 Data must be available from the start
- ⏰ Deadline 19 November; max. 15 page application.
Full text
- Original project call (German): https://www.bmbf.de/bmbf/shareddocs/bekanntmachungen/de/2021/09/2021-09-06-Bekanntmachung-Datenkompetenzen.html
- .DeepL translation in English
About the ML ⇌ Science Colab
Our mission at the ML ⇌ Science Colaboratory is to empower researchers to apply recent machine learning (ML) methods in their fields. Whether you work with texts, images, time series or simulators, we strive to help you improve your workflow for discovery.
If you are rather interested in shorter cooperation projects (without attached positions), please have a look at our cooperations program (https://mlcolab.org/ml4research).
