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Field
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apply cutting-edge machine learning algorithms, with focus on foundation models and LLMs/agents, to analyze complex biological data. This data includes gsingle cell genomics profiles, spatial data, and
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evaluate machine learning approaches for predicting clinically successful drug targets. For this work, the postdoc will have access to a large high-performance compute cluster and to AbbVie's cutting-edge
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transmitted to the larger organization. Qualifications § A PhD in Electrical and Computer Engineering, Applied Physics, or a related field § >3 years experience with Lumerical and Comsol electromagnetic
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from multiple disciplines and institutions. Required: PhD in in computer vision, machine learning, artificial intelligence, or a closely related field. Strong background in machine learning / computer
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, single-cell analysis, and machine/deep learning (preferred but not required). Strong programming and statistical skills (e.g., Python, Perl, R, Bash). Track record of first-author research papers. Strong
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servicing missions. Experience with machine learning techniques for robotic decision-making and intelligent control for tasks with high uncertainties. Experience with research on multi-agent collaboration and
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balance of supervised investigation and work experience in a learning environment that will expose the participant to activities across the drug development process. We are seeking scientists from U.S
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from sensors or other continuous data sources. Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages
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(EHR), health information exchanges, and data analysis software. Experience with health IT innovation, including working with artificial intelligence, machine learning, telemedicine, or mobile health
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AI to predict safety outcomes for multiple targets and combination therapies Collaborate with research teams and data scientists to design data-driven strategies using machine learning/AI methods