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of memory, ageing, and the effect of Alzheimer’s Disease risk factors on midlife brain function and cognition. The applicant should be interested in applying multivariate and machine learning neuroimaging
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join the group to develop AI and machine learning based software to assist clinical workflow and pre-clinical studies. Required Qualifications: Ph.D. in a physical science or engineering field Strong
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will also use focussed ion beam milling scanning electron microscopy (FIB-SEM) to prepare infected cells for in situ cryo-ET. The resulting tomographic data will be analysed by machine-learning assisted
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: Education: Ph.D. in machine learning, computer science, engineering, physical science or related technical discipline. Experience: Expertise in developing and training AI models Proficiency in Python
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for this position will work as a member of an interdisciplinary team led by Dr. Colin Xu on Department of Defense (DoD)-funded research project involving the use of statistical and machine learning methods
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The postdoctoral researcher will lead the development of computational methods for aligning cortical organisation across species using transcriptomic and anatomical data combined with modern machine
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e.g., ultra-cold gases of bosonic or fermionic atoms, machine learning technologies and quantum computing. At the same time, we work in close connection with IJCLab experimentalists, particularly
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, proteomics, metabolomics, microbiome). Strong expertise in machine learning, deep learning, and advanced AI frameworks (TensorFlow, PyTorch, Scikit-learn). Experience with bioinformatics tools and databases
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The University of Chicago Academic Jobs Postdoctoral Researcher at the Rank of Instructor Committee on Conceptual and Historical Studies of Science, Social Sciences Division Position Type: Faculty
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geospatial modeling approaches to analyze urban environmental processes. • Apply machine learning and geospatial data analysis techniques to large Earth Observation datasets. • Produce high-quality