Sort by
Refine Your Search
-
written English, ability to work both independently and collaboratively. Additional qualifications Experience or coursework in one or more of the following areas is considered an advantage: formal methods
-
education to enable regions to expand quickly and sustainably. In fact, the future is made here. Description of work You will be working in the laboratory of Marta Bally (https://ballylab.com
-
equations. Your main research assignments will be to develop new models and methods for generative sampling and Bayesian inference. You will be jointly supervised by Assistant Prof. Zheng Zhao (https
-
, and datasets; often at substantial computational and environmental costs. This PhD project targets sustainable and resource-efficient machine learning with a focus on methods that reduce compute, energy
-
experimentally driven (approximately 70/30 wet lab to modeling) and will include: Design and fabrication of 3D-printed brain tissue models with tunable transport properties Development of experimental methods
-
methods that reduce compute, energy usage, memory and storage demands, and associated carbon emissions while aiming to maintain model quality. Your work will include developing new methodologies and
-
. The department conducts undergraduate education and research in political science and peace and conflict studies. For more information, see https://www.umu.se/en/department-of-political-science/ . General
-
the flexibility of neural methods. If successful, the work has the potential to advance applications such as automated theorem proving, knowledge-graph inference, and causal analysis. The Department of Computing
-
application! Your work assignments We are looking for a PhD student to work on the development of novel spatio-temporal machine learning methods. Our world is inherently spatio-temporal, i.e. physical processes
-
and Uppsala, and will be formally established on 1 January 2026 through the merger of two existing units: the Dept. of Forest Biomaterials and Technology and the Dept. of Forest Economics. The