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language and at least one statistical package, with python/R preferred. Strong experience with high-throughput sequencing data analysis. Experience with Linux, hpc environments, version control and workflow
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in dynamical systems modeling (ODEs) and machine learning and very strong programming skills (Java, Python). A background in evolutionary genomics research is a strong plus, as is previous experience
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strong interest in foundational research very good programming skills, preferably in Python good written and spoken English skills We offer: The position comes with access to high performance computing
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data. Writing new R packages or Shiny Apps for implementation of developed methodology. Applying AI and ML tools (including Python, R, and possibly other languages) to test and evaluate biomedical
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one of the following programming languages: C++, PERL, Python, R, Java Experiences with high-throughput sequencing data (WGS, WES, RNA-Seq, ChIP-Seq) analysis Excellent oral and written communication
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methodology. Applying AI and machine learning (ML) tools (including Python, R, and possibly other languages) to test and evaluate biomedical hypotheses. Developing benchmarks and working together with staff
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: MATLAB, Python, LaTeX. • You have excellent command of written and spoken English. What we offer: Inspiring working atmosphere: You are a part of an international academic team in a healthy and fair
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quantum foundations. • You have experience in academic writing. • You should have experience with the usual tools for advanced experiments: programming experience: MATLAB, Python, LaTeX. • You have
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strongly preferred. Strong Python skills, and proficiency in PyTorch and/or JAX. Ability to reason about neural network behavior from first principles: how architectural choices, regularization, and training
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, Mobility or Climate, among others. Strong programming skills in Python/R, machine learning frameworks, and dashboarding tools (e.g., Streamlit, Superset, Grafana, PowerBI). Familiarity with various types