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utilizes a widely available diffraction-limited spinning disc confocal microscope (although not limited to this modality) for imaging. A single-step, machine-learning based approach is then applied
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in, but not limited to, the following areas are especially welcome: Reinforcement Learning Virtual Reality, Augmented Reality, Digital Avatars Embodied AI Natural Language Processing Human-Computer
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. Applicants should have strong expertise in computational analysis of electrophysiological data as well as proficiency in large language models and machine learning algorithms. First-hand experience in
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at the Assistant, Associate or Professor level. We are currently recruiting candidates with expertise in data science, machine learning, computational or systems biology, and/or bioinformatics, with interest in
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an excellent scientific track record. Proven expertise in environmental genomics, metagenomics, or large-scale omics data analysis. Experience with machine learning or AI approaches in biological data is an
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experience in computational biology and AI/machine learning (highly preferred) Physical Requirements Remaining in a normal seated or standing position for extended periods of time; reaching and grasping by
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Documenting and testing codes Improving upon existing machine learning and numerical models Your qualifications: Excellent Python programming skills, Matlab and C++ experience is a plus Interest in Space
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with experience in ligand discovery. Our research group is focused on developing state-of-the-art computational methods for ligand/drug discovery, using machine learning, high-performance/cloud computing
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ERC-funded postdoctoral fellow in theoretical developmental biology, using tools from applied mathematics, biophysics, and machine learning A talented and creative researcher is sought to take part
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R and experience with statistical analysis, machine learning methods, and high-performance computing. What we offer As well as the exciting opportunities this role presents, we also offer defined