Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Field
-
for the new green steels compositions, including impurities and tramp elements. These models should enable density-functional-theory (DFT) accurate large scale atomistic simulations of defects including
-
Prof S He Application Deadline: 29 September 2025 Details We invite applications for a fully funded four-year EPSRC iCASE PhD studentship at the University of Sheffield, offered in collaboration with SLB
-
for PhD positions. As a member of our team, you will have the opportunity to collaborate on cutting-edge technologies like quantum simulators, Bose-Einstein Condensates, and quantum information processing
-
theoretical perspectives on knowledge exchange, communities of practice and identity formation. Under the daily supervision of Prof. Daan Raemaekers (ceramic archaeology, Neolithic) and dr. Stijn Arnoldussen
-
economic impact through simulation modeling. Beyond this unique project, this position offers an exciting opportunity to advance simulation techniques in HTA! Information and application Submit your
-
Faber: email: carly.faber@uit.no or Prof. Sabina Strmić Palinkaš: email: sabina.s.palinkas@uit.no Jon Terje Hellren Hansen, Ingun A.Mæhlum via Unsplash Jon Terje Hellren Hansen, Ingun A.Mæhlum
-
are located in Copenhagen. We offer creative and stimulating working conditions in dynamic and international research environment. Principal supervisor is Prof. Jan H. Jensen, Department of Chemistry
-
dynamic and international research environment. Our research facilities include top-notch optics laboratories and access to a world-class cleanroom. Principal supervisor is Prof. Albert Schliesser (email
-
-fabrication processes for superconducting devices Automatic bring-up and calibration of quantum processors Design and simulation of quantum processors Optimal-control techniques for high-fidelity qubit
-
learning in simulated and indoor/outdoor environment. Reasonable results can be achieved in high signal-to-noise ratio environments; further research is required to improve deep learning in fast variation