1,559 machine-learning "https:" "https:" "https:" "https:" "The Open University" positions in Germany
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to environmental cues. Innovation drivers include the development of advanced technologies and the full integration of complex computational approaches to answer relevant biological questions. To learn more about
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based on our own machine learning models and it supports research in our field. The system consists of a multi-node environment, with an Elasticsearch database, data pipelines in Go and Python Data is
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PhD/Postdoc position in trustworthy data-driven control and networked AI for rehabilitation robotics
for outstanding candidates, with a successful degree (master/ diploma/doctoral/PhD) with exceptional records. A strong disciplinary background in • control, system theory and optimization • machine learning
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with those PhD and post-doc students who do research in the same cluster to encourage peer-to-peer learning across space and different cultures. The doctoral students will be encouraged to actively
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protection information of TUM. Kontakt: application.baybioms@tum.de More Information https://www.tcf.tum.de/baybioms/open-positions/bioinformatics-staff/
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environmentally friendly chemistry, in applications for the aerospace and military sectors as well as in life-cycle assessments, recycling and sustainability concepts – which you could soon help to create
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University of Munich (TUM), you will be submitting personal data. Please refer to our data protection information in accordance with Art. 13 of the General Data Protection Regulation (DSGVO) http://go.tum.de
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: active learning (uncertain cases first), smart sampling, confidence thresholds, gradations (auto-label/review/manual), measurement and decision logic for throughput vs. quality. Proficiency in programming
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packages for machine learning. You are not afraid of learning new technologies and frameworks. You enjoy developing prototypes. You are independent, creative and curious and you can work independently. What
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is expected. Background Information: Nat. Chem. 2015, 7, 105; Chem. Eur. J. 2019, 25, 4590; Angew. Chem. Int. Ed. 2019, 58, 418; Nanoscale 2021, 13, 19884. www.sengegroup.eu https://www.ias.tum.de