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affordance‑driven decisions. • Develop computational and theoretical models that bridge neural data and behaviour, leveraging modern machine‑learning toolkits. • Drive multi‑lab collaborations across SCENE; co
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technology. A recent example of our work can be found at Nature Medicine(link is external) , (PMID: 41530382) and further information on our lab can be seen at https://sinhalab.stanford.edu/(link is external
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underrepresented populations, making it essential to develop AI methods that can learn from real expert practice while meeting stringent privacy, consent, and data-governance requirements. The SCEC has developed
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information for 3 references Stanford is an equal opportunity employer and all qualified applicants will receive consideration without regard to race, color, religion, sex, sexual orientation, gender identity
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, and data science. We are especially focused on understanding the interplay between genetics, lifestyle, environment, and clinical factors on cardiovascular disease risk. Our work incorporates biobanks
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seek a highly motivated computer scientist for a post-doctoral position in our multi-disciplinary health services research center within the Department of Surgery. The post-doc will have access to unique
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priority project, while also contributing to secondary efforts. Responsibilities include gaining deep familiarity with study assessments, protocols, data structures, and—where applicable—recruitment
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. The lab values rigorous science, creativity, collaboration, and welcomes scientists from all backgrounds. Selected publications are listed below. More information can be found at: https://med.stanford.edu
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, the molecular and placental mechanisms underlying its protective effects remain poorly understood. In this translational research project, Dr Yoel Sadovsky (MD, biologist) and Dr Ivana Maric (PhD, data scientist
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will help lead research trials examining interventions for PTSD and related psychopathology, including substance use, and will have opportunities to contribute to other ongoing projects through data