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Job Description Job Alerts Link Apply now Job Title: Research Fellow (Computational Materials Science) Posting Start Date: 16/07/2025 Job Description: Job Description A postdoc position is available
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radiotherapy for cancer. This role offers the opportunity to work at the forefront of cardio-oncology science, combining sophisticated small animal radiation models, single-cell transcriptomics and state
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& Molecular Biophysics , home to a diverse array of structural and cellular biology research, which is part of the School of Basic & Biomedical Sciences . We sit in the Faculty of Life Sciences & Medicine
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, molecular immunology, and translational models. Led by Dr. William Gibson, the lab is based at Dana-Farber and Harvard Medical School and is committed to developing new therapeutic platforms that bridge
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models to predict TCR-peptide/MHC (pMHC) interactions. Utilizing structural computational biology techniques to characterize and model TCR-pMHC interactions. Designing experiments to test and validate
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, molecular dynamics, and machine learning, to model battery electrolyte and solid electrolyte interphase (SEI), while collaborating with experimentalists. Qualifications • Ph.D. in Computational Materials
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The Wu lab (https://www.lerner.ccf.org/immunotherapy/wu/) is currently seeking a highly motivated Postdoc Fellow to join our research team in the Center for Immunotherapy & Precision Immuno-Oncology
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Ph.D. in a relevant field by the time of appointment. The postdoc will be based at the Harvard University Herbaria (HUH) and will have access to all the resources available through the Department of OEB
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systematic perturbation approaches. Systems Biology: Integrate multi-omic datasets to map the molecular networks influenced by mito-MPs. Machine Learning: Apply cutting-edge protein language models and AI
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University of North Carolina at Charlotte | Charlotte, North Carolina | United States | about 16 hours ago
at Charlotte is interested in the molecular mechanisms of genome integrity and cancer etiology using Xenopus egg extracts and mammalian cells as model systems. In particular, the Yan lab has made contributions