Sort by
Refine Your Search
-
Listed
-
Country
-
Field
-
and/or Matlab, parallel programming Experience in international collaboration Fluent in English (spoken and written) Demonstrated ability to publish in international journals and present at conferences
-
leading peer-reviewed journals and conferences. Researching and developing parallel/scalable uncertainty visualization algorithms using HPC resources. Collaboration with domain scientists for demonstration
-
, excursions) Global geo-/paleomagnetic field modelling expertise is advantageous Strong programming skills, preferably in Fortran, Python and/or Matlab, parallel programming Experience in international
-
results. Machine Learning skills to automise comparison process. Unbiased approach to different theoretical models. Experience in HPC system usage and parallel/distributed computing. Knowledge in GPU-based
-
and planet formation context Experience in the field with HPC system usage and parallel/distributed computing Knowledge in GPU-based programming would be considered an asset Proven record in publication
-
invasive sensing tools to monitor metabolites, oxygen, carbon dioxide, pH, and other parameters. Ideally, the methods can function in parallel and on a large scale. The research is vital to understand key
-
platform enables us to test hundreds of different conditions in parallel and assess their impacts on human immune responses, such as antibody production. We routinely work with industry partners to exploit
-
through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Are you excited by out-of-the-box
-
. You have good programming skills in Python and/or R; you are familiar with reproducible coding and automated (geospatial) data analysis. You have excellent scientific writing and communication skills in
-
on a new project called TRUSTLINE, which is part of the Learning Introspective Control (LINC) DARPA Program. The project aims to develop machine learning (ML)--based introspection and monitoring