Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
-
Field
-
thereafter. Project description We are seeking a highly motivated PhD student to work on a joint project between the Eye Translational Research Unit at The University of Copenhagen, the Section for Visual
-
. Project Description We invite highly qualified, thorough, and motivated applicants to apply for the position. The PhD will engage in research on causal discovery and inference, and for partially identified
-
PhD scholarship in Runtime Multimodal Multiplayer Virtual Learning Environment (VLE) - DTU Construct
personalized learning for improved instant decision making. Key beneficiaries are expected to be construction industry stakeholders, for example, project owners, architects, engineers, site management (incl
-
the carbon footprint of milk production. The project will apply advanced statistical methods, artificial intelligence, and cutting-edge genetic models to support and enhance management and breeding decision
-
A PhD position starting November 1, 2025 (with some flexibility in both directions) is available at the University of Southern Denmark (SDU) for research in an exciting project in algorithmic
-
, Faculty of Arts, Aarhus University, in collaboration with the CRIES project funded by Independent Research Fund Denmark (DFF) and Center for Humanities Computing (CHC), invites applications for a PhD
-
engineering and project management is advantageous Strong analytical and technical problem-solving skills, with a solid foundation in computational engineering Ability to work independently and take initiative
-
offer computational efficiency and the ability to handle uncertainties. This project aims to identify promising RL-MPCs for application and upscaling in real-life building management settings. As PhD
-
Description A PhD position starting November 1, 2025 (with some flexibility in both directions) is available at the University of Southern Denmark (SDU) for research in an exciting project in algorithmic
-
genetics and archeology. Project description Your task will be to develop new computational methods to study archaic introgression and applying them to the largest dataset of present-day human genomes