Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Program
-
Field
-
(Sensor Informatics and Decision-Making for the Digital Transformation). Read more about the Competence Center here: https://liu.se/forskning/seddit . The focus of this specific PhD project is to explore
-
the genome (compression, optical tweezers). - Analyze the impact of forces on the final production of Twist protein. - Validate the sensitivity to forces of genes identified by NetSeq. The successful candidate
-
, inspects, tests, maintains, repairs, calibrates, and installs mechanical refrigeration and equipment, air conditioning, heating, compressed air, and vacuum systems. Tests system operations for leaks and
-
ou le béton, tirent leur cohésion des forces adhésives qui lient les grains entre eux, transformant le réseau de contacts en un système de contraintes de traction et de compression. Bien qu'efficace
-
ou le béton, tirent leur cohésion des forces adhésives qui lient les grains entre eux, transformant le réseau de contacts en un système de contraintes de traction et de compression. Bien qu'efficace
-
Great Falls College Montana State University | Great Falls, Montana | United States | about 3 hours ago
at a two-year college. Online teaching experience. Experience teaching in a compressed or accelerated non-standard semester schedule. The Successful Candidate Will Effective written, oral, and
-
: Homogenization of (in)compressible visco-elastic fluids Singular limits such as low Mach and stratification Related topics such as existence theory, especially for limiting systems The applicant must have: a Ph.D
-
experience with manufacturing and testing of adhesively bonded carbon-fibre composite joints (i.e. tensile/compression testing, fracture mechanics). 2. Direct experience in the application of atmospheric
-
extensively studied in dynamic compression, with widely varying compression rates. A large body of literature exists, but there is disagreement on the transition ranges, the nature of some of these transitions
-
, including Tikhonov regularization [3], Bayesian approaches [4], and compressive sensing or sparse regularization methods [5]. However, with the emergence of Physics-Informed Neural Networks (PINNs), new