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Field
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a position combining project management, machine-learning model development, data management/analysis, and manuscript writing for publication. Preference will be given to applicants with (1
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. Proficiency in computer programming, including scripting in Python, Fortran, or other computing tools for data processing and modeling. Experience in grant proposal writing within a collaborative environment
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conducting clinical or preclinical proof-of-concept studies Preferred: Experience in physiological signal processing and the application of machine learning to biomedical data Background in computational
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Associate will contribute to ongoing projects and have the opportunity to develop independent research aligned with the aims of the ADN lab. Current work focuses on machine learning and multivariate decoding
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qualifications include: Experience with radio interferometric observing, data processing, and imaging. Experience with modern machine learning / deep learning techniques and software packages. Experience with time
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Ph.D. in molecular biology, cell biology, biochemistry or neuroscience. Prior research experience in mouse models, and/or membrane trafficking and lysosome biology will be a plus. Interested candidates
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understanding of artificial intelligence applications and methodologies, such as working knowledge of generative AI tools, use of large language models, machine learning, and ethical frameworks for AI
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upon future funding. Qualifications Required Education and Experience Appropriate PhD in a related field. Preferred Qualifications Experience with machine learning and deep neural network techniques
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, including hybrid simulations coupling machine learning with numerical methods, multiscale discretization, nonlocal closure modeling, structure preservation, multilevel and multifidelity machine learning
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Python is required. Programming in C or C++ is a plus. Background in statistical genomics, longitudinal modeling, non-parametric statistics, machine learning and deep learning are preferred and encouraged