Sort by
Refine Your Search
-
Listed
-
Category
-
Field
-
fellow will build a library of high-resolution experimental data of oligosaccharides, against which they will critically assess the current MD models and perform data-driven optimization. The verified
-
assess the current MD models and perform data-driven optimization. The verified models will be used to reveal the conformational ensemble and dynamics of oligosaccharides in the human glycome, in
-
disorders (e.g., Cushing’s disease, metabolic syndrome, cardiovascular disease, sleep and shift work disorders). Beyond clinical applications, the research may contribute to optimizing athletic performance
-
, sleep and shift work disorders). Beyond clinical applications, the research may contribute to optimizing athletic performance, eating habits, and sleep cycles. In collaboration with Stanford University’s
-
routes to identified target compounds and using these to produce compound libraries for further evaluation in various assays. We plan to use the departments laboratory for automated chemistry to optimize
-
contribute to optimizing athletic performance, eating habits, and sleep cycles. In collaboration with Stanford University’s Center for Genomics and Personalized Medicine, we aim to advance real-time monitoring
-
of black-box SAT- and ILP-solvers in combinatorial optimization, to the inherent dependence on empirical evaluation found in common machine learning pipelines. The goal of the project is to advance methods
-
, optimization, programming theory, visualization, and didactics. Affiliated centers and labs include the Center for Data Science (CEDAS) , the Computational Biology Unit (CBU) and the Energy Informatics Lab