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, ideally with experience in generative models, reinforcement learning, or high-dimensional optimization. Programming proficiency in languages such as Python. Ability to work both independently and in a team
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learning, medical image computing, biomedical engineering, medical physics, or related field Strong Python and PyTorch experience Solid publication record and ability to communicate research results
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programming languages such as R or Python Experience with multiome data analysis (e.g. methylomics, Lipidomics, Proteomics, ATAC-seq) Proven experience with advanced computational methods such as deep and
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(e.g. fuel cells, batteries, heterogeneous catalysts, interfaces) Proficiency in high-level programming languages, e.g. Python Previous supervision of graduate students, as well as laboratory
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, systems biology, biomedical data science, cancer biology, or a related field Strong experience in omics data analysis, ideally including single-cell or spatial transcriptomics Proficiency in R and/or Python
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publications Excellent command of English Strong proficiency in programming languages such as Python, MATLAB, or R Demonstrated methodological expertise in advanced EEG and/or fMRI methods, evidenced by
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., Python, R, C/C++) and experience with high-throughput sequencing data. Solid understanding of RNA biology, transcriptomics, and epitranscriptomics. Desirable Skills Experience with Nanopore sequencing (RNA
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Solid programming skills (e.g., Python, MATLAB, C/C++ or similar) Experience in MR sequence programming is highly desirable Strong interest in translational, across-organ imaging research Ability to work
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chromatin biochemistry and in vitro reconstitution o bioinformatics workflows (R/Python), statistics, reproducible analysis o third generation sequencing (e.g. Oxford Nanopore) fluent English language
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analysis is expected; familiarity with scientific programming environments (e.g. Python, R, or similar) is highly desirable interest in policy-relevant science and sustainability frameworks strong motivation