Sort by
Refine Your Search
-
implementation of novel training strategies under experimental constraints, e.g., active learning and other data-efficient approaches Conduct large-scale benchmarking and comparative evaluation of gene
-
., active learning and other data-efficient approaches Conduct large-scale benchmarking and comparative evaluation of gene perturbation models across diverse single-cell datasets Collaborate closely with
-
of Health (LIH) is seeking a highly motivated Postdoctoral Researcher with specialized expertise in multi-omics data analysis. You will play a central role in analyzing large datasets from multiple large
-
of atomic environments Detection of extrapolation and low-reference data regimes Active learning in configurational and chemical space Training and benchmarking of large-scale foundational MLFF models More
-
, headed by Prof. Grégoire Danoy. PCOG conducts research in parallel computing, search and optimisation techniques, to provide efficient, scalable and robust solutions to state-of-the-art, large-scale
-
Autonomous Transportation. As far as technical enablers are concerned, we leverage expertise on advanced technologies including semantic/task-oriented data processing, signal processing, network resource
-
backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud Computing, Cryptography, Satellite Systems, Vehicular Networks, and ICT Services
-
backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud Computing, Cryptography, Satellite Systems, Vehicular Networks, and ICT Services
-
, reinforcement learning, robust or explainable models). • Knowledge of Network Digital Twin concepts. • Experience working with large, real-world datasets and building reproducible pipelines (data quality, missing
-
the detection of zero-day vulnerabilities, and (2) enable continuous cybersecurity assessment of software. More specifically, the project will investigate the use of multimodal large language models and fuzzing