Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Program
-
Field
-
, patient motion, and more. Today, these parameters are either manually configured, heuristically optimized, or compensated post hoc using multi-level calibration scans or corrections, which introduces
-
them to optimize any results, working to obtain new tool compounds and drug candidates. Leveraging state-of-the-art computational methods, including structure-based ultra-large virtual screenings
-
optimize deep learning models, trained for the reconstruction of events generated with this simulation framework and targeting their application on a distributed trigger system based on several processing
-
SUSMAT-RC - Postdoc Position in Computer-Aided Design and Discovery of Sustainable Polymer Materials
staff position within a Research Infrastructure? No Offer Description Job description: We are seeking a highly motivated and skilled postdoctoral researcher to join our dynamic team in the Sustainable
-
Research Framework Programme? Horizon Europe - ERC Is the Job related to staff position within a Research Infrastructure? No Offer Description We are seeking a postdoctoral researcher with interest and
-
biological disciplines. Insights in immunology, oncology, neuroscience, and/or drug discovery are considered beneficial. WHO WE ARE LOOKING FOR PhD in biosciences or a related field, with postdoctoral
-
successful candidates will join the GravNet-IFAE group, in charge of developing and optimizing all theoretical aspects of the proposal. This includes the complete modeling and simulation of the response
-
towards co-optimized solutions that maximize full-duplex MIMO performance. As a postdoctoral researcher, you will also play a central role in driving the future research agenda, supervising PhD students
-
welcome you to apply for a postdoctoral position at the Department of Information Technology, Uppsala University. Uppsala University has a long tradition of successful research – among its alumni are 16
-
simulations and multiscale spatial-omics data. • Integrate uncertainty quantification into scientific machine learning workflows and optimize the design of computational (ABM) and wet-lab experiments