Sort by
Refine Your Search
-
Listed
-
Country
-
Employer
- Nature Careers
- Technical University of Denmark
- CNRS
- MOHAMMED VI POLYTECHNIC UNIVERSITY
- University College Cork
- AALTO UNIVERSITY
- Chalmers University of Technology
- Aalborg University
- Aarhus University
- Cornell University
- Forschungszentrum Jülich
- National Aeronautics and Space Administration (NASA)
- Oak Ridge National Laboratory
- Rutgers University
- Stanford University
- Technical University of Munich
- UNIVERSITY OF SYDNEY
- University of Amsterdam (UvA)
- University of North Carolina at Chapel Hill
- University of Sydney
- XIAN JIAOTONG LIVERPOOL UNIVERSITY (XJTLU)
- Aalborg Universitet
- Centrum Badan Kosmicznych PAN
- Delft University of Technology (TU Delft)
- European Space Agency
- FUNDACIO INSTITU DE RECERCA EN ENERGIA DE CATALUNYA
- Fondazione Bruno Kessler
- IMEC
- King's College London
- Lund University
- Luxembourg Institute of Science and Technology
- Max Planck Institute for Solar System Research, Göttingen
- National Renewable Energy Laboratory NREL
- Radboud University
- Riga Stradins University
- The Ohio State University
- The University of Iowa
- Tilburg University
- UNIVERSITY OF HELSINKI
- Universitat de Barcelona
- University of Basel
- University of Birmingham
- University of Colorado
- University of Florida
- University of Luxembourg
- University of Oxford
- University of Oxford;
- University of Texas at Arlington
- University of Twente (UT)
- Université côte d'azur
- Uppsala universitet
- 41 more »
- « less
-
Field
-
length scales Develop machine learning algorithms to support process optimization, predictive modeling, and intelligent manufacturing control Integrate simulation tools with in-situ sensor data from
-
attention to scientific rigor and interpretability Experience with XAI tools (SHAP, LIME, Integrated Gradients) to identify which features of the model are driving the predictions Clear written and verbal
-
combine density functional theory (DFT), molecular simulations, and machine-learning force field (ML-FF) development to uncover the factors controlling NHC–surface interactions and to model realistic
-
Postdoctoral Researcher in ML for Dynamical Systems Representation, Prediction, and State-estimation
to develop machine learning-enabled approaches for predictive modelling and state estimation for fundamental applications within physical sciences. Your role The main research responsibilities involve building
-
Postdoctoral Researcher in ML for Dynamical Systems Representation, Prediction, and State-estimation
for predictive modelling and state estimation for fundamental applications within physical sciences. Your role The main research responsibilities involve building cutting edge machine learning techniques
-
. Preferred Qualifications Domain knowledge in power system operations, economics, and planning problems. Experience with control theory concepts (e.g., Model Predictive Control, Dynamic Programming) and their
-
modern workflow managers (e.g. Nextflow, Snakemake) and version control; support for novel wet-lab protocols for DNA methylation analysis and nanopore sequencing; and development of predictive models
-
or more of the following areas: Advanced Process Control and Optimization Digital Twin and Modeling & Simulation Predictive Maintenance and Fault Diagnosis Industrial IoT and Edge Computing Good programming
-
on Nanoparticles You will develop atomistic models and machine-learning potentials to interpret experimental data and predict catalytic performance. The tasks can include: Advancing equivariant neural network
-
19 Mar 2026 Job Information Organisation/Company Aarhus University Research Field Engineering Other Researcher Profile First Stage Researcher (R1) Recognised Researcher (R2) Positions PhD Positions