Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Employer
- University of Oslo
- University of Bergen
- UiT The Arctic University of Norway
- INESC TEC
- Nanyang Technological University
- National University of Singapore
- Research Centre on Child Studies
- Rudjer Boskovic Institute
- Tampere University
- UNIVERSITY OF SOUTHAMPTON
- UNIVERSITY OF SURREY
- University of Birmingham
- University of Stavanger
- FEUP
- Harvard University
- Indiana University
- Institute of Czech Literature of the Czech Academy of Sciences
- Instituto Politécnico de Coimbra
- Lawrence Berkeley National Laboratory
- Leibniz
- NTNU - Norwegian University of Science and Technology
- National Research Council Canada
- Ohio State University
- Queen's University
- Ruđer Bošković Institute
- SWPS University
- Universidade de Coimbra
- University of Agder
- University of Antwerp
- University of British Columbia
- University of California
- University of Inland Norway
- University of Michigan
- University of New South Wales
- University of North Carolina at Charlotte
- University of Nottingham
- University of South-Eastern Norway
- University of Surrey
- University of Sussex;
- University of Tasmania
- Western Norway University of Applied Sciences
- 31 more »
- « less
-
Field
-
modern control theory (PID, adaptive, robust, and fractional control); Experience with fuzzy logic and AI-based control (reinforcement learning, neuro-fuzzy systems); Skills in modelling and simulation
-
for wireless communication systems, including modulation and coding techniques on the physical layer of a radio, array antennas and their use in multiple input multiple output (MIMO) wireless connectivity. Very
-
for wireless communication systems, including modulation and coding techniques on the physical layer of a radio, array antennas and their use in multiple input multiple output (MIMO) wireless connectivity. Very
-
: Strong expertise in signal processing for wireless communication systems, including modulation and coding techniques on the physical layer of a radio, array antennas and their use in multiple input
-
developing synthetic datasets using simulation environments. Familiarity with the theory and implementation of diffusion models and GANNs applied to the same context. Minimum requirements: • Knowledge
-
research interests encompass a broad range of topics, including discrete mathematics, finite model theory, and the complexity of logical systems, as well as the foundations of AI, explainability, and answer
-
theory & experiment: Co‑design validation experiments with experimentalists; iterate models using feedback from new measurements. Automate the workflow: Build Python workflows for simulation and data
-
& advance digital twins: Integrate electronic structure (e.g., DFT, ab initio MD, tight-binding) with multiscale simulations to predict experimental observables at interfaces. Bridge theory & experiment: Co
-
measurement quality issues related to respondent non-compliance in ecological momentary assessment or exploring the use of machine learning techniques to aid the estimation of item response theory (IRT) models
-
at the interface between data analysis and theory. We are also open to employing data-driven techniques if the candidate wishes. The ocean is currently evolving with the changing climate, and we are curious