Sort by
Refine Your Search
-
Listed
-
Country
-
Program
-
Employer
- Forschungszentrum Jülich
- Northeastern University
- Ecole Centrale de Lyon
- Lawrence Berkeley National Laboratory
- Oak Ridge National Laboratory
- University of California
- Brookhaven Lab
- Brookhaven National Laboratory
- CNRS
- INSTITUTO DE ASTROFISICA DE CANARIAS (IAC) RESEARCH DIVISION
- Luleå University of Technology
- National Renewable Energy Laboratory NREL
- UNIVERSITY OF VIENNA
- University of A Coruña
- 4 more »
- « less
-
Field
-
distributed intelligence across the computing continuum. In this role, you will have the opportunity to lead and contribute to cutting-edge research aimed at transforming scientific data management and
-
Experimental Sciences or equivalent training programs; - PhD Degree in Chemistry; - Training in DFT and CASSCF computational methods and molecular dynamics studies; - Experience in physicochemical and structural
-
areas. Qualifications To be eligible for a postdoc position, you must have a PhD in Computer Science, Automation, Electronics, Mechatronics, Industrial IT, or another relevant subject area. The PhD should
-
FieldMathematicsYears of Research ExperienceNone Additional Information Eligibility criteria Academic: PhD in applied mathematics, computer science, or medical physics. Scientific interests: applied mathematics
-
funded through the EU Research Framework Programme? Horizon Europe - ERC Reference Number HORIZON-ERC-2024-ADG Is the Job related to staff position within a Research Infrastructure? No Offer Description
-
distributed computing or HPC environments. Additional Information: Brookhaven Laboratory is committed to providing fair, equitable and competitive compensation. The full salary range for this position is
-
to experimental data from photon-counting or time-resolved detectors. Experience with Bayesian methods, uncertainty quantification, or real-time data processing. Familiarity with distributed computing or HPC
-
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
-
such as aeroacoustics. Furthermore, the high scalability on massively parallel computers can lead to advantageous turn-around times for industrial applications. The Laboratory of Fluid Mechanics and