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. Expertise in Python is expected. A demonstrated ability to conduct research and produce scholarly outputs, as evidenced by publications in peer-reviewed journals. Familiarity with molecular and cellular
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clear orientation toward transdisciplinary collaboration. Proficiency in one or more relevant programming languages (e.g. R, Python, NCL, Julia, Fortran) and evidence of effective scholarly communication
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should have experience developing, implementing, or applying computational methods to large-scale biological datasets. Expertise in Python and/or R is expected. Experience with biological data processing
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computational analysis of proteomics data is highly desirable. Experience with Python, R, or related scientific computing tools; proteomics software platforms; biological databases; data repositories
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, implementing, or applying analytical or computational models to molecular and cellular systems. Expertise in Python, R, MATLAB, or related scientific computing tools is desirable. The successful candidate should
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. Preferred Experience in genomic data analysis, computational biology, statistical genetics, or functional genomics. Proficiency in R, Python, Linux/Unix, and high-performance computing environments
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Postdoctoral fellow within Microglia–Neural Circuit Interactions in Memory and Disease (PA2026/2262)
with in vivo calcium imaging (either neurons or glia) Experience with microglia biology or neuroimmune interactions Behavioral experiments Solid data analysis skills (e.g., MATLAB or Python for calcium
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. Applicants are expected to have strong programming skills in Python, hands-on experience with PyTorch, and practical experience with GPU computing. Experience with engineering simulation, computational
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Language Models Time-Series Data Prediction and Modeling Intelligent Decision-Making and Optimization Algorithms Strong programming skills (proficient in Python, PyTorch/TensorFlow, etc.). Strong
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studies of organic, organometallic, photoredox, radical, or homogeneous catalytic systems. Fluency with Python and modern scientific computing workflows; experience with Git, HPC clusters, SLURM, Gaussian