Sort by
Refine Your Search
-
with collecting and analyzing data gathered from human subjects, both in field, clinic and lab studies as part of evaluations of the technology. A large part of the role will focus on supporting a
-
cutting-edge theories, methods, and computational tools for integrating large-scale, heterogeneous biomedical data across multi-institutional research networks, with a focus on the analytical and
-
is research excellence and fit with the lab’s focus. More information on the lab’s research is available here . We especially encourage candidates with proven experience in applying computational and
-
such as Data Science, Statistics, Computer Science, Epidemiology, Environmental Health, or a related field. Demonstrated expertise in large scale analysis and familiarity with health-related datasets
-
command of data wrangling, cleaning, and large-scale dataset management. Machine Learning/Deep Learning: Experience with PyTorch, TensorFlow, or Hugging Face; embedding models; and model validation
-
of claims data and related large administrative datasets to support policy-relevant research related to mental health and addiction services utilization and quality of care. Experience working with Medicaid
-
such as: Causal inference and the design and analysis of experiments Reinforcement learning and sequential decision-making Analysis of complex systems, networks, and large-scale data Machine learning
-
econometric methods to administrative and other large-scale datasets—particularly claims data—to support policy-relevant research on competition and regulation in the U.S. pharmaceutical market
-
opportunity to contribute to a high-impact, large-scale project investigating the evolution of cephalopods and their fascinating venom systems! As a Postdoctoral Fellow, you’ll be at the forefront of a cutting
-
that solve big problems. We support research that universities, companies, and venture capital firms don’t fund because they view it as too risky. We prefer to use the word “challenging,” and we love