81 parallel-computing-numerical-methods-"Multiple" research jobs at Aarhus University
Sort by
Refine Your Search
-
Listed
-
Country
-
Program
-
Field
-
University. Dr Speed's research involves developing statistical methods for better analysing data from genome-wide association studies (GWAS), with a particular focus on improving our understanding of human
-
The Section for Electrical Energy Technology at the Department of Electrical and Computer Engineering (ECE), Aarhus University, is in a phase of rapid growth in both education and research
-
The Department of Biomedicine, Faculty of Health, Aarhus University invites applications for a postdoctoral position in Computational Spatial Proteomics and Multi-Omics Integration, starting 1
-
The Department of Ecoscience at Aarhus University invites applications for two postdoctoral positions to strengthen our research on image recognition, computer vision and deep learning applied
-
at the Department of Electrical and Computer Engineering, Aarhus University, where we are advancing communication-efficient and distributed foundation model inference across the computing continuum
-
This is a full-time (37 hours/week) on-site role located in Aarhus, Denmark for a Postdoctoral Research Fellow at the Department of Computer Science, Aarhus University. This position is for 2 years
-
, or numerical methods. Your job responsibilities As a Postdoc in Quantum Enhanced MRI your position is primarily research-based but may also involve teaching assignments. You will contribute to the development
-
across multiple scales. The Pioneer Center Land-CRAFT was established in June 2022 to undertake fundamental and applied research from field to landscape scales that will address these societal challenges
-
, neuroscience and personalised medicine. The Department of Biomedicine provides research-based teaching of the highest quality and is responsible for a large part of the medical degree programme. Academic staff
-
substantial knowledge and research experience in areas such as computational fluid dynamics, turbulence modeling, data-driven methodologies, machine learning, and parallel computing. The candidate should also