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FieldComputer scienceEducation LevelMaster Degree or equivalent Skills/Qualifications Strong foundations in Machine Learning and Deep Learning Excellent Python programming skills Experience with PyTorch
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Biology: Development of deep learning, graph neural network, generative AI, and RNA foundation models to analyze large-scale omics, spatial transcriptomics, ribonomics, and imaging datasets. Application
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/Qualifications Strong research track record in AI and scientific applications. Excellent knowledge of Machine Learning and Deep Learning. Strong Python programming skills. Experience with PyTorch, TensorFlow
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Learning. Experience with the deep learning ecosystem and high-performance computing infrastructures. Experience designing and conducting experiments with human participants is a strong plus. Experience in
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Brandenburgische Technische Universität Cottbus | Cottbus, Brandenburg | Germany | about 2 months ago
candidate is expected to incorporate innovative approaches into their research that connect classical probabilistic models with modern deep learning architectures. Examples include Bayesian deep learning
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about applying deep learning to decode the regulatory grammar of plant genomes and translating predictions into testable biological hypotheses, we invite you to join the Omics Data Analysis and
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strong interest in foundational research in the above-mentioned research areas strong programming skills, preferably in Python, including experience with deep learning frameworks (e.g., PyTorch, TensorFlow
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and experience with modern deep learning frameworks (e.g. PyTorch) Solid background in machine learning, ideally with experience in NLP, large language models, or sequence modeling Interest in clinical
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Karlsruhe Institute of Technology - Institute of Applied Geosciences - Division of Geothermal Research | Karlsruhe, Baden W rttemberg | Germany | 3 months ago
learning and deep learning workflows for automatic signal classification, including supervised, unsupervised, and/or semi-supervised (hybrid) approaches to use both labeled and unlabeled data. Model
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Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung | Bremerhaven, Bremen | Germany | 2 months ago
on global climatic changes. In particular, the project aims to assess the role of convection in the vertical exchange of climate-relevant tracers such as carbon and heat between the surface and deep