Sort by
Refine Your Search
-
future therapeutic strategies. The Opportunity This role is designed for a postdoc seeking increased scientific independence, leadership responsibility, and strong mentorship within a collaborative
-
learning applications in healthcare Strong problem-solving skills and ability to work independently and collaboratively Excellent communication skills and fluency in spoken and written English Demonstrated
-
, including conference travel and grant-writing experience, within a highly collaborative environment that bridges basic neuroscience and clinical research. In addition to leading the primary neuroimaging trial
-
care for patients requiring urgent or emergent intervention. The fellowship provides comprehensive training in data engineering, exploratory analysis, statistical modeling, machine learning, and artificial
-
approaches to remove atmospheric particulate (e.g., PM2.5) pollution. The math-based subgroup focuses on the use of deep learning and generative AI to address critical problems for the electric grid and broad
-
, machine learning, statistics and programming skills (R and Python) is preferred. Record of peer-reviewed publications. Knowledge in one or more of the following areas is desirable: single-cell profiling
-
of urothelial exfoliation in cancer therapeutics. The labs are committed to fostering a highly collaborative and scientifically rigorous environment. This position offers an excellent opportunity to learn about
-
into clinically feasible solutions for liver cancer patients. Aligned with this goal, this position offers exciting opportunities to work with external collaborators to evaluate promising diagnostic probes and
-
for Human and Planetary Health, an interdisciplinary Center at the Woods Institute for the Environment in close collaboration with the Center for Innovation in Global Health at the School of Medicine
-
involve both method development and applied research, with opportunities to publish in leading journals, present at top conferences, and contribute to open-source tools. Collaboration with clinicians, data