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Field
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for the management and support of cyber security services across multiple environments including on premises, public, and hybrid cloud. This role requires knowledge and hands-on experience in implementing and
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model performance across multiple development iterations. This hands-on experience will provide valuable insight into the application of AI and geospatial technologies in environmental research. What
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range of individuals, including students, staff, faculty, machinists, external vendors, etc. Strong organizational and time management skills Ability to balance interruptions across multiple and varied
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Lawrence Berkeley National Laboratory has multiple openings for a Scientific Engineering Associate in Berkeley, CA. Duties: Perform scientific data analysis using the scientific python stack
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phenotyping of health outcomes at multiple time-points. S/he will work within a diverse, highly collaborative, and multi-disciplinary research environment and interact with world leaders in the fields of cancer
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Professor Arbel’s lab in the context of a grant focused on developing multi-modal causal deep learning models to predict future disability progression and treatment response in Multiple Sclerosis
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Specialist to join our innovative team. The Research Data Management Specialist will: Manage multiple datasets and corresponding documentation, visualize data, and work closely with the analytic team
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Engineering, or a related discipline. Proficiency in Java and/or Python programming. Familiarity with software development tools and platforms (e.g., IDEs, cloud environments etc). Demonstrated ability
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. The ideal candidate will also be expected to have quantifiable experience with: A variety of different neuroimaging methodologies. Using multiple programming languages, including R, Python, MATLAB and
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acquired at multiple resolutions (tissue-level, single-cell/nucleus, and spatial transcriptomic data), requiring complex integrative analyses. The successful candidate will lead the analysis of a large