Sort by
Refine Your Search
-
Country
-
Employer
- U.S. Department of Energy (DOE)
- MOHAMMED VI POLYTECHNIC UNIVERSITY
- University of Luxembourg
- Duke University
- Oak Ridge National Laboratory
- Empa
- Institute of Photonic Sciences
- Lawrence Berkeley National Laboratory
- Potsdam-Institut für Klimafolgenforschung e.V. (PIK)
- Stanford University
- UNIVERSITY OF SYDNEY
- University of North Carolina at Chapel Hill
- ADELAIDE UNIVERSITY
- Aalborg University
- Aarhus University
- Bournemouth University;
- Chalmers University of Technology
- Cornell University
- Delft University of Technology (TU Delft)
- Inria, the French national research institute for the digital sciences
- KTH Royal Institute of Technology
- KU LEUVEN
- MUNSTER TECHNOLOGICAL UNIVERSITY
- National Aeronautics and Space Administration (NASA)
- National Energy Technology Laboratory (NETL)
- Royal Holloway, University of London;
- Singapore-MIT Alliance for Research and Technology
- Technical University of Munich
- Texas A&M AgriLife
- Texas A&M University
- Umeå University
- University of Amsterdam (UvA)
- University of Antwerp
- University of Arkansas
- University of California
- University of Chicago
- University of Florida
- University of Graz
- University of London
- University of South Carolina
- University of Sydney
- Université de Caen Normandie
- Veterinärmedizinische Universität Wien (University of Veterinary Medicine Vienna)
- Zintellect
- 34 more »
- « less
-
Field
-
and process engineering to develop, evaluate and improve electrochemical reactors and their supporting systems. We are particularly interested in candidates with practical experience in electrolysers
-
technologies for sustainable chemical production and energy conversion. You will combine hands-on experimentation with device and process engineering to develop, evaluate and improve electrochemical reactors and
-
methods for evaluating cotton fiber quality and identifying characteristics that promote reliable, predictable dye uptake. Through this experience, you will gain hands-on exposure to analytical
-
U.S. Department of Energy (DOE) | Washington, District of Columbia | United States | about 6 hours ago
. Working in coordination with the White House, Capitol Hill, other federal agencies, and local stakeholders, the Office of Policy aims to facilitate an affordable, reliable, and secure energy economy and
-
to advance the development and application of reliable, interpretable and uncertainty-aware machine learning methods for high-stakes regulated domains, including law, finance, policy and regulatory decision
-
. Must have a desire to design, execute, analyze, archive, review wet lab experiments in a manner that is scientifically justifiable, reliable and understandable to others under the guidance of your
-
research profile focuses on development of novel statistical methods and software for the analysis of large and complex data sets. Applications include e.g., evaluation of large-scale achievement tests, and
-
competitiveness, bolster energy security-related initiatives, strengthen reliability of the energy grid, support the energy workforce, and increase affordability for families and businesses through a wide range of
-
sediment observations from existing datasets; evaluating impacts of expanded datasets on watershed-scale assessments; developing and maintaining open-source software tools and R packages; disseminating
-
generally, the project is part of a large initiative at Serval and SnT, which aims to support the reliable deployment of machine learning systems by providing industry actors with practical evaluation tools