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-throughput workflows, materials databases, or machine learning for materials. Familiarity with GPU/parallel Python or with modeling disorder and alloys Job Duties Develop and implement methods for disordered
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Biological & Life Sciences Division – Postdoc Researcher: AI for Precision Medicine and Therapeutics
, machine learning, programming in C, C++, Python Scripting languages and MATLAB, using a parallel computing environment Bioinformatics, network biology, network medicine, network analytics, AI, ML, DL, LLMs
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research is MAGESTIC (https://doi.org/10.1038/nbt.4137 ), a CRISPR-based technology that enables precise engineering of thousands of defined mutations in parallel, in a single test tube. By linking each
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automated or high-throughput experimental systems (e.g., robotic solid/liquid handling, parallel reactor platforms). Experience with automated process control, data acquisition, and database integration
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quantify the impact of fast, tenuous shocks on ionized line emission. In parallel, high-resolution 3D MHD simulations of fast shocks interacting with dense interstellar clouds will be carried out with
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foundation models, directly advancing the frontier of computational biology and machine learning. You will also implement parallel systems capable of training such models across large GPU clusters on cryoSTEM
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the following areas is preferred, and an exceptionally strong candidate in a single area is also encouraged to apply. Relevant areas include: Parallel and distributed graph and or ML algorithms
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(e.g. weather, hydrology). Expertise in data and model parallelisms for distributed training on large GPU-based machines is essential. Candidates with experience using diffusion-based or other generative
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society and has diversity as a core value. Therefore, everyone, regardless of personal background and orientation, is encouraged to apply for the position. Aalborg University has a policy of parallel
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to candidates having a strong record in developing novel computational strategies to solve complex physics problems with relevant experience in nonlinear analysis of pdes and parallel computation. FLSA Exempt