17 parallel-processing-bioinformatics Postdoctoral research jobs at University of Amsterdam (UvA)
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prestigious ERC Consolidator Grant in a great interdisciplinary institute in Amsterdam. Join us! Are you passionate about machine learning, natural language processing and generative AI? We are seeking a
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the BEAT project. In parallel, qualitative research methods, especially from affective interaction design, are used to capture the emotional and experiential aspects of navigating urban spaces. These methods
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; Model relevant processes (e.g., bedload sediment transport, sediment connectivity); Mentor MSc and BSc students (potentially also PhD researchers); If desired, take on teaching responsibilities in
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, usable optical systems such as laser lock circuits and laser sources, iterating quickly based on experimental results and feedback. In parallel, you will contribute to prototyping, validating, and
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mechanisms that underlie memory consolidation during sleep, specifically examining how these processes are disrupted in the context of Alzheimer’s disease (AD). You will investigate how these molecular
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two crucial research questions: how do materials degrade in solution and solid phase, and what is the (extent of) correlation between these processes? While PhD candidates will design and apply new
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Engineering » Process engineering Researcher Profile Recognised Researcher (R2) Application Deadline 15 May 2026 - 21:59 (UTC) Country Netherlands Type of Contract Temporary Job Status Not Applicable Hours Per
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Models to push the frontier where computer vision, physics simulation, and embodied AI converge. Join Us! This position is part of a collaborative research programme between the University of Amsterdam
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) are facing a critical methodological juncture. While commercial AI tools like ChatGPT offer powerful capabilities for text analysis and coding, they act as black boxes that obscure how data is processed, pose
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of the parameter space in relation to the statistical model. One of the main goals of SLT is to quantify the complexity of such models w.r.t. the data generating process (and some prior probability distribution