242 phd-studenship-in-computer-vision-and-machine-learning Postdoctoral positions in Germany
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)! Tübingen has a long history of academic excellence (founded in 1477; DNA was discovered here ; linked to 11 Nobel laureates) and is an innovation center in medicine and machine learning. About Eberhard
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Physics Theoretical Physics / Complex systems including applications to biology Complex Systems (more...) Computer Simulation Fluid Mechanics Appl Deadline: 2025/09/30 11:59PM (posted 2025/07/22
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Max Planck Institute for Dynamics and Self-Organization, Göttingen | Gottingen, Niedersachsen | Germany | 2 months ago
compact, lightweight and robust holographic instruments Develop real-time data pipelines using edge computing, built on our existing toolchain and enhanced with machine learning tech-niques Validate
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of computer vision and machine learning. The positions are fully-funded with payments and benefits according to German public service positions (TV-L E13, 100% for PhDs and TV-L E14, 100% for PostDocs; 45k
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Ph.D. or equivalent degree in mathematics, physics, computer science, bioinformatics, or a related field Experience in developing deep learning models Ideally, prior experience in analyzing biological
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Germany Application Deadline 21 Sep 2025 - 21:59 (UTC) Type of Contract To be defined Job Status Other Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job
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in an area of safe machine learning and/or applications in healthcare Management of a team of PhD students, postdocs, and software developers Coordination of the implementation of research prototypes
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research on the topic outlined above is paramount Candidates are expected to be interested in working at the boundaries of several research domains PhD degree in computational biology, bioinformatics
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, particularly in C++ and Python Good communication skills in spoken and written EnglishInterest or prior experience in machine learning techniques is considered an asset. You may expect a multifaceted and
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, enrichment analyses - biological interpretation of data Your qualification - PhD/MSc degree in bioinformatics, computer science, mathematics, life sciences - background in Machine Learning and/or RNAseq