147 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" "UCL" positions at Nature Careers in Germany
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the usual documents until 1/11/2026 on the application portal of the university using this link: http://obp.uni-goettingen.de/de-de/OBF/Index/76205 . For more information get in touch with Serena Müller
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exciting research opportunity in a multidisciplinary and international research institution with a collegial and flexible working environment. Participation in the BioMed X Boot Camp where you learn how
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biophysics, computational biology, mathematics in the life sciences, computer science and machine learning with application to biological systems, and related areas. What we provide The CSBD provides fully
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outstanding researchers with a strong track record of advancing the state of the art in machine learning and potentially its application to biology and biomedicine, with the ambition to build an internationally
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Postdoc (f/m/d) on Generative AI for de Novo Protein Design / Completed university studies (PhD) ...
for Advanced Systems Understanding (CASUS) is a German-Polish research center for data-intensive digital systems research. The Department of Machine Learning for Infection and Disease is looking for a Postdoc (f
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, Süddeutsche Zeitung). Learn more about our research at www.erturk-lab.com . We are seeking a highly motivated AI Scientist (best: Computational Pathologist / Machine Learning Scientist for Digital Pathology) (f
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Professor (W3 / W2 with Tenure Track to W3) for Materials and/or devices for Photonics and Quantum T
quantum technologies. This research can be complemented by digital methods of process simulation and optimization, as well as machine learning. Requirements include an outstanding PhD in materials science
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Senior Semantics Data Scientist (m/f/d) in the fields of Computer Science, Data Science, Physics, Ma
key role in the foundation of interoperable, machine-readable data platforms, powering AI analyses and automated workflows. You will collaborate with top scientists from all subject areas at BAM
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the transfer of new ideas from the lab to real-life applications, improving lives. The Theis Lab at the Computational Health Center is internationally recognized for pioneering methods in machine learning
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research group “Machine Learning for Biomedical Data” led by Prof. Dominik Heider and is embedded in the DFG-funded Collaborative Research Centre 1748, Principles of Reproduction. The CRC 1748 involves