Sort by
Refine Your Search
-
Listed
-
Country
-
Field
-
with neuroimaging, numerical mathematics, optimization, inverse problems, software development, motivation and research interests. The location for this research will be the workgroup of Prof. Dr
-
-of-the-art sparse algorithm in matrices, tensor and networks for large-scale numerical, scientific and AI models and disseminating findings through publications and presentations in top-tier peer-reviewed
-
to numerous preclinical research projects focused on the development of novel molecular magnetic resonance imaging (MRI)-based techniques for early detection, disease phenotyping and monitoring treatment
-
testing, and advanced process simulation, with the objective of optimizing grinding performance and enhancing resource recovery. The ideal candidate will have a strong background in mineral processing
-
scientists with numerous international collaborations and partnerships and have funding from the National Institutes of Health and the Canadian Institutes of Health Research. This position will join a diverse
-
machine learning—for chemical and biological applications. You will design and implement models ranging from molecular to process scales, develop model-predictive control and optimization strategies, run
-
institutions, and a research and development provider for numerous companies throughout the world. The INM is a member of the Leibniz Association and has about 250 employees. The INM research group
-
University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 29 days ago
professionalism, enhance learning, and create personal and professional sustainability. We optimize our partnership with the UNC Health System through close collaboration and commitment to service. OUR VISION Our
-
Associate. This postdoctoral researcher will work under the supervision of Prof. Bo Ji and Prof. Lingjia Liu, conducting research on immersive communication/computation-aware optimization of next-generation
-
experimental and numerical approaches. Materials classes of interest include components (monomers, polymers, additives, (nano)particles, etc.) utilized in high-performance polymeric materials with relevance in