63 phd-sandwitch-in-architecture-and-built-environment Postdoctoral positions in Finland
Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
-
Field
-
Researcher Profile First Stage Researcher (R1) Recognised Researcher (R2) Positions PhD Positions Country Finland Application Deadline 3 Oct 2025 - 16:15 (Europe/Helsinki) Type of Contract Temporary Job Status
-
Architecture – Department of Architecture Location: Otaniemi Campus, Espoo, Finland Join a cutting-edge research environment where architecture, landscape architecture, and artificial intelligence meet to
-
to take part in the supervision of PhD students and the teaching activities of the research group. Your network and team Currently, our research group consists of 1 professor, 1 lecturer, 1 staff scientist
-
and have a PhD in a field related to mathematical modeling and experience in optimizing industrial processes, this might be something for you! We are looking for a postdoctoral researcher (“PostDoc”) to
-
the Department of Architecture at Aalto University, which offers a vibrant, interdisciplinary environment bridging architecture, landscape, and urbanism with emerging technologies and sustainability research Your
-
are Professor Mika Pettersson and Dr. Andreas Johansson at the Department of Chemistry and Nanoscience Center (JYU). The project deals with the development of a novel nerve-machine interface built from graphene
-
a dynamic, international research environment. Your experience and ambitions Required Qualifications PhD in Electrical Engineering, Physics, Photonics, Materials Science, or related field Strong
-
-immunology-program-trimm YOUR QUALIFICATIONS We are looking for ambitious researchers with a PhD, a solid publication record, and strong background in some of the following experimental/computational areas
-
Researcher to join the group. The research project is concerned with the challenging problem of modeling the complex modern radio environment, where a diverse set of devices and agents share the available
-
collaborators. Your work will develop algorithms, inference methods, and frameworks to adapt models from training data to test environments, which is necessary to resolve distribution shifts, hidden confounders