Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Employer
- Oak Ridge National Laboratory
- European Space Agency
- University of Washington
- AMADE research group
- Aalborg Universitet
- Delft University of Technology (TU Delft)
- Duke University
- Fermilab
- Forschungszentrum Jülich
- Georgia Institute of Technology
- KTH Royal Institute of Technology
- King Abdullah University of Science and Technology
- North Carolina State University
- Northeastern University
- SUNY Polytechnic Institute
- Technical University of Munich
- Tilburg University
- 7 more »
- « less
-
Field
-
, multidisciplinary team environment. Preferred Qualifications: Knowledge of uncertainty quantification methods and causal inference for complex environmental systems. Experience with large-scale Earth system
-
networks, risk analysis or uncertainty quantification (preferred). Knowledge of data science in general as well as practical experience with conducting data science analyses with good programming skills
-
of Lepton Number Violation to nuclear transition operators, computation of relevant many-body LNV operators in light nuclei for benchmarking and uncertainty quantification purposes, and the broader
-
, United States of America [map ] Subject Area: Uncertainty Quantification for Life Sciences Appl Deadline: (posted 2025/10/01, listed until 2026/04/01) Position Description: Apply Position Description North Carolina State
-
candidates with strong expertise in Bayesian methods, uncertainty quantification, and/or machine learning applied to nuclear theory. The group’s research spans a wide range of topics including nuclear
-
? Which disruptive technologies or paradigms (specific architectures, lightweight adaptation methods, xAI, interpretable-physic awareness, uncertainty quantification, etc.) will you explore? Why is this
-
Associate who will focus on creating innovative uncertainty quantification and visualization algorithms that enable trusted visual representation and analysis of large-scale 2D/3D scientific data
-
: · Experience with neutrino data analysis, MeV-scale nuclear reactions, nuclear data evaluation, and/or uncertainty quantification techniques · Experience in developing physics event generators and/or other Monte
-
, Uncertainty quantification, Approximation Theory, Applied Probability and Bayesian statistics, Optimal Control and Dynamic Programming. Appointment, salary, and benefits. The appointment period is two years
-
improved performance in tasks of systems analysis like parameter estimation, solving inverse problems, and uncertainty quantification. The successful candidate will join a multi-institution research team