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(intracranial and scalp EEG) and MRI data sets. Develop and implement algorithms for data processing and interpretation. Collaborate with clinicians and researchers to design studies and analyze results. Present
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algorithms in extremely complex and enormously large spaces motivated by physics and chemistry Developing interpretable AI for scientific discovery in physics (example here ) Formal mathematics (using Lean’s
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), Neha Potnis (Auburn), Courtney Leisner (Virginia Tech)) and Thomas Lahaye (Tübingen)) to investigate the effect of fluctuating temperatures on the outcome and evolution of plant-pathogen interactions. We
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Are you interested in making a real difference in the area of biomedical data science? This role will provide an excellent opportunity to further develop knowledge and experience as a post-doctoral
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to, benefit-harm analysis of cancer early detection tests, development of clinical decision rules in cancer early detection leveraging Electronic Medical Records (EMRs), and development of EMR-based algorithms
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Are you interested in making a real difference in the area of biomedical data science? This role will provide an excellent opportunity to further develop knowledge and experience as a post-doctoral
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within tissues using our in-house developed spatial transcriptomics-based technology (Spatial VDJ). Using established and newly developed algorithms, we map B cell evolution within tissues, including class
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will have the opportunity to develop innovative algorithms and models that integrate multiple data modalities, collaborate with industry partners, and contribute to high-impact publications. Job
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data collection and management Data analysis and model building Develop advanced deep learning and machine learning algorithms Assist with organizing large scale multimodal neuroimaging datasets, brain
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on transplant using multimodal medical data. You will be responsible for literature review, data cleaning, model development and implementation. You should possess a relevant PhD (or near completion) in