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lab in Stanford’s Psychiatry Department, led by Neir Eshel, MD, PhD. We are looking to hire curious and ambitious postdocs to join our team. Lab projects focus on the neural circuitry of reward-seeking
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, biologics, and cannabis. Apply statistical and machine learning approaches (e.g., sequence analysis, latent class analysis, clustering) to examine medication use trajectories and patient subgroups
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applications for a postdoctoral fellowship position to join a project investigating trafficking risks in charcoal supply chains in Brazil. The position is open to recent graduates of PhD programs in statistics
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focuses on translational research at the intersection of bioelectronics, healthcare-focused nanofabrication, and emerging applications of machine learning in radiology. Our team operates within a state-of
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. Required Qualifications: Doctoral degree (PhD) conferred by start date Demonstrated experience with analysis of large health databases Training and experience in machine learning and deep learning methods
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will be determined based on factors including (but not limited to) the qualifications of the selected candidate, budget availability, and internal equity. Pay Range: $86,100 Aligning Machine Learning
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, clinicians, and researchers with research-backed assessments to advance learning, accelerate reading research, promote understanding of learning differences, and foster equitable access to high-quality, data
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significant contributions to Palestinian studies. The postdoctoral scholar will teach one course each year in their host department: an undergraduate-level course in the first year, a graduate-level course in
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. Qualifications for this position include a PhD in Computer Science, Artificial Intelligence, Natural Language Processing, Human-Computer Interaction, or a closely related field. Candidates should have demonstrated
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benefit from additional training in clinical research. You will: Obtain broad knowledge about the fields of pain and SUD neurobiology. Acquire depth and expertise in an area of specialization within pain