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analysis and multi-omics data integration workflows using Python/R Integrate digital pathology data with omics data (e.g., MS-based proteomics, spatial proteomics) Develop and drive independent project ideas
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biology, or a related field Experience designing, executing, analyzing, and interpreting quantitative experiments, including high-throughput screens. Experience with coding software such as Python, R, and
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physiology Competency in scientific programming (e.g. ImageJ, Python) for data analysis and image processing. About the Lab & Environment. The Krishnakumar lab is a highly collaborative group with access
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programming and instrument control using Matlab, Python, Labview etc Machine / deep learning expertise Strong analytical skills and ability to work in a multidisciplinary team Excellent communication and
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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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with biological datasets; experience with R, Python, or omics analysis pipelines is advantageous but a keen willingness to learn is equally valued Language Requirements: Applicants must demonstrate
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, BWA, STAR, GATK, VarScan, DESeq) Proficiency in Linux and programming languages such as Python, R, MATLAB, or Perl Excellent written and verbal communication skills in English, along with a
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science/AI, bioinformatics, or related fields. Strong research capability, interdisciplinary communication skills, and proficiency in scientific English are required. Experience in AI/ML, programming (Python/R
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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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Research Assistant (m/f/d) with a Ph.D. in Civil Engineering, Engineering Physics, Physics, Mathemat
., using FEniCSx) Advanced knowledge of scientific programming, preferably in Python, including experience with implementing machine‑learning methods (e.g., PyTorch) Excellent spoken and written English, as