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Field
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with biological tissue. Duties of the position will include designing optical spectroscopic imaging technology, using numerical simulation and machine learning tools to extract diagnostically-relevant
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machine learning—for chemical and biological applications. You will design and implement models ranging from molecular to process scales, develop model-predictive control and optimization strategies, run
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networks; experience in applying machine learning models and processing imagery from UAS and satellite platforms. Other Requirements: Willingness to work irregular hours and in occasionally adverse weather
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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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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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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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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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cardiovascular treatments. In this role you will apply both machine learning predictive modelling and human genetic analyses of non-coding regulatory sequences to identify cell-specific targets for coronary artery
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d) excellent written, oral communication skills e) strong data analysis skills. Ideal applicants will also have experience with some combination of: a) Machine learning e) code optimization and
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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