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, vegetation, and water table position on energy transmission. Co-develop and apply process-based numerical models of dune morphological change informed by collected datasets. Coordinate field campaigns
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additional AD risk genes and to develop disease models. Work on the projects studying molecular mechanisms that recently identified Alzheimer’s disease risk repeat expansion variants contribute to disease
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clinical features using machine learning and foundational modeling approaches. This work supports disease modeling across chronic kidney disease, acute kidney injury, cancer, and neurological conditions. A
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influence placental physiology, fetal development and long-term health outcomes. The successful candidate will join a dedicated research team conducting translational studies using animal models, human tissue
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structural elucidation, and (iii) synthetic chemistry and biocatalysis for the preparation and evaluation of antibody-drug conjugates (ADCs) as the next generation anticancer therapies by site-specific
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)-statistics, (applied) mathematics, or a related STEM field. Prior working experience with EHR data, machine learning, NLP, bioinformatics, and large language models (LLM) is preferred. In particular
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. The research interests of the group include beyond Standard Model phenomenology, dark matter, cosmology, and gravitational waves. The UF particle theory group includes Professors Jeff Dror, Yohei Ema, Rachel
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as cell culture, gene editing, IP, WB, flow cytometry, etc. Epigenetics/Genomics approaches: ChIP, ChIP-seq/CUT&RUN, ATAC-seq, RNA-seq, CRISPR Screening, etc. Expertise in in vivo animal models
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benefits package. Required Qualifications: PHD in astronomy or physics. Preferred: Experience with large-scale structure data and software development. Special Instructions to Applicants: For full
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neurodegenerative diseases and iPSC-derived neurons representative of the disease. Testing promising compounds for their in vivo pharmacokinetic properties in wildtype and mouse models for neurodegenerative diseases