Sort by
Refine Your Search
-
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
-
The successful candidate will join the Serval research group and work on a large research project related to Machine Learning Security and Testing. The subject of the thesis will be “Real-World
-
variants of the sodium channel Nav1.1, which are associated with different forms of epileptic syndromes and migraine. The aim of the project is to use machine-learning assisted molecular dynamics simulations
-
We are looking for a doctoral candidate with a strong computational, engineering, data scientific or machine learning background that is keen to work in an interdisciplinary environment and open to
-
integrating local flexibility markets through distributed AI-based coordination, market mechanism design, and cloud-to-edge computing. It aims to develop scalable machine learning methods for coordinating grid
-
We are seeking a highly motivated PhD candidate with a strong interest or background in AI as well as in one or more of the following areas: Generative AI, Natural Language Processing, Deep learning
-
application of machine learning algorithms to automatically classify freshwater benthic diatoms at the species level and quantify key morphological traits. These advancements aim to improve ecological
-
I-2503 – PHD IN EXPLAINABLE AI FOR DATA-DRIVEN PHYSIOLOGICAL AND BEHAVIORAL MODELLING OF CAR DRIVERS
Master’s degree or Engineer diploma in Computer Science, Artificial Intelligence, Data Science, Machine Learning, or a related field. Experience and skills · Strong knowledge of AI, Machine Learning
-
integrating local flexibility markets through distributed AI-based coordination, market mechanism design, and cloud-to-edge computing. It aims to develop scalable machine learning methods for coordinating grid
-
, mMTC and URLLC Machine learning/deep learning techniques and Artificial Intelligence for wireless communications Reinforcement learning, active learning, transfer learning, federated learning and