197 parallel-computing-numerical-methods-"Simons-Foundation" positions at Technical University of Denmark
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treatment, with extensive knowledge of experimental methods in both microbiology (e.g., bioinformatics) and wastewater biotechnology. Are skilled in the development and optimization of biological processes in
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and machine-learning methods (AI/ML) to extract novel biological insights that drive our translational and fundamental research programmes. In addition to your research leadership, you will play a
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of the general degree programmes at DTU. For information about our enrolment requirements and the general planning of the PhD study programme, please see DTU's rules for the PhD education . We offer DTU is a
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(e.g., based on physiological signals or direct inputs from occupants) and developing algorithms, including machine learning methods. The work will include statistical modelling, data-driven modelling
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on the development of regulatory tools to improve CRISPR-Cas editing for neurological diseases. You will work with a wide range of methods, including molecular biology, culture and differentiation of human iPSCs
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to computational tools like RFdiffusion, ProteinMPNN, or AlphaFold. Experience with mammalian cell culture in two and/or three dimension Ability to perform biochemical and imaging methods Strong analytical skills
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well as abroad. To support your success, you will have access to DTU National Food Institute’s excellent laboratory facilities. Your overall focus will be to assess if the current biocide assessment methods based
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: Background in Data Science, Computer Science or related fields; Working experience in implementing AI models (not just loading pre-trained model). PyTorch framework is preferred; Experience with APIs
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PhD scholarship in Runtime Multimodal Multiplayer Virtual Learning Environment (VLE) - DTU Construct
leading universities, research institutes, and industrial partners across Europe to deliver a world-class doctoral training programme in risk assessment, resilience engineering, and smart technologies. Its
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will include: Integrating new scientific methods into our Fortran and Python-based tools, and verification and validation of the resultant implementations Supporting large-scale geospatial global and