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and CHIP-seq. · Expertise in downstream analysis and biological interpretation of bioinformatic findings · Proficiency in R/Python programming, developing analysis pipelines and
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, sufficient programming fluency (e.g., Python; familiarity with common ML tooling) to run computational experiments, and excellent communication skills, including writing for publication and presenting results
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publishing high-quality research papers in top-tier conferences and journals. Proficiency in advanced programming and computational modeling tools (e.g., Python, distributed systems). Good written and oral
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motivated Postdoctoral Fellow with strong expertise in RNA-seq and multi-omics data analysis. Candidates should be proficient in Python and/or R and have a solid background in Biology, Computational Biology
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RAS signaling and/or targeting is preferred Expertise in computational biology/bioinformatics (including proficiency in Python/R) would be desirable, though this skill is not essential Prior experience
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cellular neurophysiology or related fields Experience in patch clamp-based electrophysiological recording from native neurons Expertise in programming with Python and R Experience with programming
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quantum many-body theory with a focus on quantum impurity models (particularly Kondo model). Strong computational skills (with Python or Julia or C++ or Matlab or equivalent) and using numerical techniques
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microscopy, antibody-based techniques, small molecules/ligand-trap based therapies Preferred qualifications Experience with bioinformatic analysis using R and/or Python. Experience with molecular/cellular
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in C or C++ or a track record of mastering multiple low-level and high-level programming languages (e.g., Python, R, Julia, Fortran). Department Contact for Questions Questions pertaining
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: - Proficient in programming languages such as Python, with experience in using AI/ML libraries (e.g., TensorFlow, PyTorch, scikit-learn). - Familiar with high-performance computing (HPC) environments and