Sort by
Refine Your Search
-
Listed
-
Country
-
Employer
- Nature Careers
- Duke University
- University of Cambridge
- ;
- Brookhaven Lab
- DAAD
- Imperial College London
- Luxembourg Institute of Socio-Economic Research (LISER)
- National Institute for Bioprocessing Research and Training (NIBRT)
- The University of Chicago
- University of Lund
- University of Zurich Blockchain Center
- Uppsala University
- Wageningen University and Research Center
- 4 more »
- « less
-
Field
-
-specific challenges in deploying distributed AI for power system control. The outcomes will be invaluable to electricity system operators, flexibility aggregators, and the broader energy research community
-
vibrant research environment supported by robust infrastructure and extensive collaborative networks. Expected start date and duration of employment This is a 1–year position from 1 September 2025 or as
-
The Luxembourg Institute of Socio-Economic Research (LISER) is recruiting aPhD Candidate in Geospatial Data Science and Environment with a focus on Artificial Intelligence and Machine Learning (f/m
-
-specific challenges in deploying distributed AI for power system control. The outcomes will be invaluable to electricity system operators, flexibility aggregators, and the broader energy research community
-
, manipulate large datasets, visualise data and perform numerical and statistical analysis is a requirement. Experience in handling 'big data', machine learning and working in distributed teams, is useful
-
the distribution of mechanical loads in the wind farm, thus also extending the lifetime of the wind farm. Your PhD project is integrated into the Living Lab 70 GW Offshore Wind, which researches crucial aspects
-
communication skills, be strongly motivated, and work well in a team setting. A rough effort distribution for this position is indicated below: · Work on assigned projects (~80%) · Review scientific literature
-
The Interdisciplinary Science (IS) Department, in collaboration with others, is performing research in the areas of renewable integration and grid modernization. The goal of our research is to