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to therapeutic discovery You bring PhD in computational biology, bioinformatics, computer science, or related field Strong coding skills (Python required; ML frameworks preferred) First-author publication(s
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neurodegenerative mouse models Experience in developing image analysis workflows (Python, MATLAB, R, Imaris) Experience in histologic post hoc brain tissue analysis (IF, IHC, RNAScope) Experience in antibody
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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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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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. Familiarity with programming languages such as MATLAB and Python, and the ability to work with large imaging datasets Excellent communication and presentation skills, with the ability to prepare high-quality
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analysis of high-dimensional data (e.g., single-cell RNA-seq, phylogenetics, spatial data). Experience in R or Python. Application instructions: Please send a CV and a brief cover letter describing your
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methodologies: optogenetics, calcium imaging, viral tracing, tissue clearing, murine behavioral phenotyping, machine-learning behavioral analysis Familiarity with programming languages (e.g. R, Python) and an
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For Someone Who • Has a PhD in computational biology, genomics, bioinformatics, microbiology, or a related field. • Is fluent in Python/R and Unix-based workflows. • Has experience with microbial genomics
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Geosciences, Environmental sciences, Civil or Environmental Engineering, Physics or Mathematics or a related discipline Experience in programming (e.g., Python, MATLAB, or similar), interest in machine learning