Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Employer
-
Field
-
experimentation and thermodynamics calculations. Establish a high-throughput bulk materials processing route to enable efficient characterisation and parallel testing of multiple compositions. Develop a high
-
experimentation and thermodynamics calculations. Establish a high-throughput bulk materials processing route to enable efficient characterisation and parallel testing of multiple compositions. Develop a high
-
has also been developing physics-based machine learning algorithms for three dimensional seismic modeling, imaging and inversion using high performance computation including parallelization on GPUs
-
, e.g. Python, Matlab, C; Experience utilizing high-performance computing (HPC) to parallelize workflows; Excellent work planning and issue resolution skills; Strong technical, written, and verbal
-
in programming, e.g. Python, Matlab, C; Experience utilizing high-performance computing (HPC) to parallelize workflows; Excellent work planning and issue resolution skills; Strong technical, written
-
We are looking for a Research Fellow to join the Department of Aeronautics and Astronautics at the University of Southampton, UK. You will be working under the supervision of Prof. Andrea Da Ronch
-
Ageing Research (https://metacoglab.org ). About the role This post is funded by a UKRI Frontier Research (ERC Consolidator) Award entitled “Computational components of conscious awareness” held by Prof
-
research with both industry and academic partners, with a willingness to work in new technical areas related to the programme and parallel projects. Prior direct experience of successful PhD student co
-
to include programming and computational modelling as core elements. Questions about the position Prof. Dirk Linke dirk.linke@ibv.uio.no For questions regarding Jobbnorge, please contact HR Adviser Nina Holtan
-
frameworks. Position 2 – Commander4: Massively parallel joint Bayesian end-to-end analysis of past, present and future CMB experiments, supervised by Prof. Hans Kristian Eriksen (h.k.k.eriksen@astro.uio.no