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biology, bioinformatics, genomics, statistics, physics, or a related quantitative field Demonstrated ability to analyse large-scale sequencing data using R, Python or equivalent A self-motivated team player
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‑on experience in single‑molecule microscopy, skills in optics or photonics, and proven ability in developing software for imaging analysis, particularly using Python. Your ability to work independently while
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, SAS or Python. Excellent written and verbal communication skills. Experience analyzing real-world health, clinical, or biomedical data. Demonstrated ability to work independently and collaboratively in
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is a plus. Candidates should also demonstrate strong skills in Python (for ML/NLP tasks) and R (for statistical modeling or data analysis), as both will be actively used in the research workflow
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genomics approaches. Familiarity with computational analysis (e.g., Python, R, Bash) and/or genome-scale data integration. Experience with cell culture and functional genomics (e.g., CRISPR/Cas9), cancer
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). Strong programming and statistical skills (e.g., Python, Perl, R, Bash). Track record of first-author original research papers. Strong oral and written communication skills. To apply, please send a cover
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will lead the programming of R/Python packages for the analysis as well as adapt existing and develop new research methodologies and training materials. You will report research findings in the form
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. Proficiency in Python, MATLAB, or R. Strong quantitative and analytic skills. Preferred Qualifications Experience with evidence-accumulation models (DDM, sequential sampling, Bayesian models). Experience with
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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