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Field
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statistical software & machine learning (e.g., R, Python, SAS, or STATA). Experience working with large population dataset (e.g. EHR, claims data). Background in health informatics, population health research
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single-cell and bulk RNA sequencing, and with bioinformatic and computational analysis (R, Python, TCGA, GSEA, QIIME2, MetaboAnalyst, or equivalent). Experience with correlative analysis of human clinical
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-resolution microscopy such as STORM, and longitudinal live-cell imaging. Transcriptomic analysis, including bulk RNA sequencing or single-cell RNA sequencing. Computational analysis in R or Python
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reproducible methods to complex population, clinical, and molecular data using R, Python, SAS, or related tools, with well-documented code and analytic workflows. Collaborate and communicate effectively with
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, computational modeling, and data analytics. Experience leading full-scale structural testing. Proficiency in Python or equivalent programming language. Experience with high-performance and high-throughput
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record. Preferred Prior experience with spintronic materials or beyond-CMOS device platforms. Familiarity with MATLAB or the Python scientific stack. Prior involvement in multi-PI collaborations
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programming/scripting (Bash,Python) Preferred Qualifications The candidate should have demonstrated experience in molecular modelling, particularly in the areas of biophysics or material design (all atom
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R or Python programming Tissue culture techniques Animal models Interest in translational cancer research, immunotherapy, and neuro-oncology. Other Requirements Ability to work with patient-derived
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development, programming (Python, Julia, C++, Fortran, etc), and excellent oral and written communication skills are required. Additional qualifications The ideal candidate has experience in developing
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or CP2K on massively parallel architectures. Solid skills in common scientific programming languages, in particular languages such as FORTRAN, C, C++, and Python Experience in parallel programming with one