Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
-
Field
-
19 Sep 2026 Job Information Organisation/Company University of Oulu Research Field Biological sciences » Other Computer science » Other Mathematics » Statistics Medical sciences » Other Researcher
-
learning – and we are growing and seeking: Postdoc / PhD Student / Entrepreneurial Postdocs to join the Institute and its wider research community. We welcome applications across all areas of machine
-
centres as controllable electricity loads. Topics include temporal and spatial shifting of computing workloads, the use of on-site energy storage and backup capacity, thermal flexibility and waste heat
-
community. We are particularly interested in candidates with: Strong computational and bioinformatics expertise combined with interest in cancer biology and gene regulation. Background can be PhD or even MSc
-
Schleuning (Senckenberg Biodiversity and Climate Research Centre, Germany). Together, the team combines expertise in ecological networks, spatial ecology, conservation science, and biodiversity informatics
-
superconductivity, quantum materials, Josephson electronics, open quantum systems, flat-band physics and momentum space topology. The group currently consists of three senior researchers, seven postdocs and four PhD
-
them in scientific papers. Collaboration with other team members and supervision of MSc and PhD students are part of the work. The position has a trial period of 6 months. Requirements The ideal
-
other researchers (MSc and PhD students, post-docs and project researchers), as well as with an extended network of international collaborators. Job description The selected candidate will work on the ERC
-
strong focus on digital data and methods. The successful candidate is expected to benefit from and collaborate with other team members, including the PI and approximately ten other researchers (MSc and PhD
-
. Essential qualifications PhD in computational statistics, bioinformatics, systems biology, or a related field. Strong expertise in statistical methods, including machine learning approaches, for analysis