Postdoctoral Researcher in Machine Learning

interested in theoretical foundations, methodological advances, or applications across the lab’s research agenda. Our research bridges computer science, applied mathematics, and biomedical sciences. We develop mathematically grounded machine learning methods and study their interpretability, reliability, and generalization, with applications in imaging, biology, and medicine. Our work connects fundamental questions about learning with challenges in scientific discovery and biomedical data analysis. The postdoctoral researcher will combine set research expectations as well as have flexibility to shape a research program with Prof. Sulam, building on their expertise and interests. Potential directions include, but are not limited to: • Foundations of machine learning, including learning theory, sparse and structured representations, optimization, and generalization. • Interpretable and trustworthy AI, including explainability, robustness, fairness, uncertainty quantification, and statistical guarantees. • Generative modeling and inverse problems, including diffusion models, learned priors, and computational imaging. • Machine learning for biomedical and scientific discovery, including medical imaging, digital pathology, neuroscience, and biomarker discovery. Projects may focus on any one area or connect several. We also welcome new directions that complement or extend the lab’s work. The researcher will develop and carry out original research, communicate findings through publications and presentations, and contribute to the lab’s collaborative research environment. Qualifications Candidates should hold a Ph.D. or equivalent doctoral degree by the start date in computer science, applied mathematics, statistics, electrical or biomedical engineering, physics, or a related field. We seek evidence of research independence, strong analytical and/or computational skills appropriate to the proposed work, and the ability to communicate and collaborate effectively. Expertise in one or more relevant areas is welcome; candidates are not expected to have experience across all listed topics. Prior biomedical research experience is not required. Application Instructions (1) a CV, (2) a brief statement of research interests, and (3) contact information for 2–3 references. In your statement, describe your past work and the questions you would be excited to pursue in the lab. You may identify connections to current research or propose complementary directions. Applications will be reviewed on a rolling basis until the position is filled. We welcome applicants from diverse academic backgrounds and research experiences. Learn more about the lab and its work at https://jsulam.github.io/. Equal Employment Opportunity Statement Salary Range The referenced salary range represents the minimum and maximum salaries for this position and is based on Johns Hopkins University's good faith belief at the time of posting. Not all candidates will be eligible for the upper end of the salary range. The actual compensation offered to the selected candidate may vary and will ultimately depend on multiple factors, which may include the successful candidate's geographic location, skills, work experience, internal equity, market conditions, education/training and other factors, as reasonably determined by the University. Total Rewards Johns Hopkins offers a total rewards package that supports our employees' health, life, career and retirement. More information can be found here: https://hr.jhu.edu/benefits-worklife/ . 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