Aleksei Tiulpin

Weill Cornell Medicine / Weill Cornell Imaging at NewYork-Presbyterian and Cornell Tech are recruiting a Postdoc for research in machine learning , medical imaging , and AI for preventive medicine . The position is in the Intelligent Medical Systems Laboratory (IMEDS) , led by Professor Aleksei Tiulpin , based at the Department of Radiology, Weill Cornell Medicine, New York City. The lab develops machine learning methods and tools for diagnostics, treatment, and scientific discovery across diseases, organs, and modalities, with special expertise in chronic non-communicable conditions such as osteoarthritis and low back pain . Research themes highlighted by the lab include scalable methods, multimodal data analysis, trustworthy AI, and deployable healthcare technologies. The postdoc will work closely with national and international healthcare leaders and top faculty in AI and medical imaging. Relevant study areas and keywords include computer science , medical science , biomedical engineering , statistics , machine learning, diagnostics, predictive modeling, and clinical imaging. No funding amount, deadline, or formal eligibility checklist is stated in the post excerpt. Interested candidates should review the lab website for the full opportunity details and application instructions. Website: https://imeds.ai

Weill Cornell Medicine / Weill Cornell Imaging at NewYork-Presbyterian / Cornell Tech is recruiting a Machine Learning Postdoc for the Intelligent Medical Systems Lab (IMEDS) in New York City. The lab is led by Aleksei Tiulpin and focuses on machine learning , medical imaging , and AI for preventive care, diagnostics, and treatment of chronic conditions. Research themes highlighted on the lab website include scalable, trustworthy, and deployable methods for healthcare, with special expertise in musculoskeletal and chronic disease imaging such as osteoarthritis and low back pain. This postdoctoral opportunity is aimed at candidates with a strong computational background and excellent software engineering skills. The post explicitly asks for agency, creativity, clear communication in spoken and written English, and a strong publication record (around three first-author top conference papers or equivalent). The position is based at Weill Cornell Medicine in New York City and offers the chance to work with leading experts in machine learning and medical imaging, with access to large datasets and clinically meaningful problems that aim to improve early disease detection and prevention. Application materials requested: a 1-page CV, a 1-page research statement, and the names and emails of two referees. The post also notes that successful candidates will be invited to give a talk at the Department of Radiology. Apply via the linked Cornell postdoctoral opportunities page or contact the lab using the email provided in the post.

Weill Cornell Medicine / Weill Cornell Imaging at NewYork-Presbyterian / Cornell Tech is recruiting a Machine Learning Postdoc for the Intelligent Medical Systems Laboratory (IMEDS) in New York City. The lab is led by Aleksei Tiulpin and focuses on machine learning, medical imaging, AI for diagnostics, preventive care, and chronic disease research . Current research themes include scalable and trustworthy ML methods, multimodal imaging, uncertainty-aware modeling, and clinically deployable tools for early detection and prevention of disease. This opportunity is especially relevant for candidates with a strong computational profile and interest in healthcare AI, medical image analysis, and translational research. The postdoc will work with leading experts and have access to large-scale clinical data, with the goal of building technology that can make a real impact on patients’ lives. Eligibility highlights: computational background, strong communication skills in English, excellent software engineering ability, and a proven publication record (around 3 first-author top conference papers or equivalent). Application materials: 1-page CV, 1-page research statement, and names/emails of two referees. Application route: email the materials to [email protected] and review the formal job posting at the Cornell postdocs page. The post mentions a 2-year postdoctoral appointment. Research keywords: machine learning, medical imaging, AI for diagnostics, preventive medicine, chronic disease, uncertainty-aware learning, multimodal models, computational medicine.

Weill Cornell Medicine is recruiting a Postdoctoral Fellow in Artificial Intelligence for Medicine to join the Intelligent Medical Systems Laboratory (IMEDS) in New York City, led by Prof. Aleksei Tiulpin . The role sits in the Department of Radiology and focuses on machine learning , medical imaging , and clinically relevant AI for early disease detection , disease prevention , and prevention of treatment complications. The lab works on methods at the intersection of computer vision , large language models , and statistics , with applications in preventive care and translational medicine. Research themes mentioned include vision-language models, alignment, implicit neural representations, image segmentation, and longitudinal disease phenotyping. The lab also highlights access to a strong clinical team, large datasets, and collaborations across biomedical engineering, AI, and medicine. Eligibility highlights: applicants should hold a Ph.D. in Computer Science or a related field and have at least three first-author publications in strong ML/CV or medical AI venues. The post also prefers candidates with mentoring experience, fellowship success, and interdisciplinary collaboration experience. Funding and terms: this is a two-year postdoctoral appointment with a salary range of $74,692–$86,535 plus benefits. The posting notes possible visa support through J-1 and H-1B options. How to apply: email a 1-page CV, 1-page research statement, and the names and emails of two references to [email protected] . Applications received by 2026-04-10 will receive full consideration. Relevant links include the lab website ( imeds.ai ) and the official postdoctoral opportunity page at Weill Cornell Medicine.