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protein engineering, computationally designing antibodies, nanobodies, and binding proteins with condition-dependent activity. You will develop deep learning and generative models for binder design
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diseases using deep learning & high resolution remote sensing data Faculty in Stanford Medicine are seeking to appoint a Postdoctoral Research Fellow to join a project developing and validating deep
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machine learning, deep learning, foundation models/LLM. Excellent quantitative and analytical skills. Strong written and interpersonal communication skills. Strong motivation & ability to work
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Helmholtz Association of German Research Centres | Geesthacht, Schleswig-Holstein | Germany | about 2 months ago
data. Manage preferences for further information and to change your choices. Accept all cookies Reject optional cookies Skip to main content Postdoctoral Researcher - Probabilistic Deep Learning for
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, benchmarking and deploy them for applications. The ideal candidate would be a PhD in geophysical sciences, computer science, or machine learning with experience in developing and verifying deep learning
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expected to have: A doctorate in a Machine-Learning related field A deep knowledge of Control Theory, both classical and deep learning based A solid publication record in top level ML venues such as
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. Your profile Applicants should hold a PhD in computer science, bioinformatics, or a related field, or expect to complete it before the start date. They should have research experience in deep learning
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. The project is conducted in collaboration with the deep probabilistic programming group of Thomas Hamelryck : https://di.ku.dk/english/research/groups/machine-learning-in-biology/?pure=en/persons
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intelligence, starting 1 April 2027. You will design new sequence-to-expression deep learning models that predict gene expression from DNA sequence in plants, using new experimental datasets generated in the
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experience with the PyTorch library and running deep learning models. The successful candidate will work closely with a team of researchers and faculty members in the ClinicalNLP lab led by Dr. Hua Xu