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antigens, T cell receptor (TCR) and antigen interactions and their crucial role in anti-cancer immune responses. You'll leverage your strong background in computational biology, machine learning, and
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on machine learning or classical force fields. 3. Familiarity with open-source coding practices (GitHub/GitLab). More Information Location: Kent Ridge Campus Organization: College of Design and Engineering
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nanofabrication is required. The postdoc is also expected to collaborate with other researchers to apply nanoelectronics and flexible electronics in biological and medical research. Basic Qualifications: Ph.D. in a
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related to battery materials, correlated electron calculations, including via DFT+U, supercells, dynamical mean field theory or experience in defect and/or alloy calculations, machine learning, and other
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and machine-learning methods (AI/ML) to extract novel biological insights that drive our translational and fundamental research programmes. In addition to your research leadership, you will play a
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at the intersection of mitochondrial biology, functional genomics, and machine learning. This interdisciplinary initiative focuses on discovering, decoding and engineering mitochondrial microproteins (mito-MPs) with
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work that underpins the scientific research of the collaboration. Research Title: Coupling Computation and Machine Learning to evaluate PFAS Chemicals The work will entail: The position is for a
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projects as well as general research involving the application of methods from theoretical physics, mathematics, and machine learning with the goal to understand the brain function. Postdoctoral Fellowships
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organoids will be plus. Dry lab: Highly motivated candidates with a PhD/MD degree in bioinformatics, genome science, systems biology, biomedical informatics, computational biology, machine learning, data
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Kannapolis and UNC Charlotte in Charlotte. Experience in yeast genomics, RNA-sequencing, bioinformatics, or machine learning is preferred. Departmental Preferred Experience, Skills, Training/Education