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extreme weather forecasting, employing data science models as developed in computer vision and natural language processing (NLP). This project leverages the large-scale high-performance computing (HPC
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-transcriptional gene regulation; kidney biology or polycystic kidney disease; mouse genetics, transgenic mouse models, and animal phenotyping; mammalian cell culture, primary cells, or kidney organoids; or RNA
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with the bone marrow microenvironment to drive clonal expansion and disease progression, with a particular emphasis on the JAK2V617F mutation. Using genetically engineered mouse models, transplantation
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that connect single-cell and spatial transcriptomic data to mechanistic, biophysically grounded models of gene regulation. There is also scope to work on exact and approximate solutions of stochastic models
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, ligand GaMD). ● Experience building and interpreting Markov State Models or comparable approaches for identifying metastable states and conformational transitions. ● Proficiency in Python and
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, including periodical/literature search and utilizing specialized skills in spectroscopy and instrumentation to analyze the collected data, with numerical models. ● Participate/assist in manuscript writing
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data beyond the application of established pipelines OR experience developing mathematical or statistical models of biological systems. ● A record of publishing computational biology (broadly defined
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field in hand by May 2026. Preferred Qualifications: Experience in Thermal Spray Materials/Processes/Characterization/Modeling. Experience in Solid Mechanics/Thermomechanics/Finite Element Analysis
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models (rodent handling/surgery experience a plus). ● Familiarity with quantitative/computational approaches (e.g., R, Python, image analysis, statistics) is a plus but not required. ● Ability
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intraperitoneal and intravenous (tail-vein) injections. Preferred Qualification: Research Lab experience in cancer cell biology and cell motility/migration in prostate cancer models. Hands-on experience in