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interfaces. Plan controlled ablation studies and reproducible evaluations using scratch training across multiple seeds, exact train and validation metrics, parity and error analyses, gradient checks, and end
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framework for unsupervised deep imaging phenotyping and imaging GWAS. The lab is now expanding these programs across pangenome informatics, clinical deployment-oriented AI, and multimodal imaging genetics
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large GPU clusters on cryoSTEM datasets in the multi-terabyte range. This position plays a pivotal role in supporting ongoing, high-impact research programs within our lab. The successful candidate will
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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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. Applicants are expected to have strong programming skills in Python, hands-on experience with PyTorch, and practical experience with GPU computing. Experience with engineering simulation, computational
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programming skills in Python, MATLAB, C++, or similar scientific computing environments, including high-performance and GPU computing. A strong scientific track record, evidenced by high-quality publications
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Recognised Researcher (R2) Application Deadline 18 Aug 2026 - 21:59 (UTC) Country Sweden Type of Contract Temporary Job Status Full-time Is the job funded through the EU Research Framework Programme? Not
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) Application Deadline 13 Aug 2026 - 00:00 (UTC) Country United Arab Emirates Type of Contract Permanent Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU
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will create a personalized training and development plan with the supervisor. Minimum Qualifications Currently has or is in the process of completing a PhD, MD/PhD, DPhil or equivalent terminal degree