25 programming-"AcademicTransfer" PhD scholarships at Chalmers University of Technology in Sweden
Sort by
Refine Your Search
-
We are offering a WASP, The Wallenberg AI, Autonomous Systems and Software Program, funded PhD position that provides a unique opportunity to develop deep expertise in robotics, machine learning
-
implementation. About the project Reactive synthesis refers to the automatic generation of programs from high-level behavioral specifications. This approach plays an increasingly important role in areas such as
-
, for example a 4-year bachelor's degree is accepted. The position requires strong verbal and written communication skills in English. About WASP Wallenberg AI, Autonomous Systems and Software Program (WASP) is
-
artificial intelligence is transforming human culture and collective memory. The Wallenberg AI, Autonomous Systems and Software Program – Humanity and Society (WASP-HS) is a national research program in
-
competitive performance. This position is supported by the Wallenberg AI, Autonomous Systems and Software Program (WASP). WASP is Sweden’s largest individual research program ever, a major national initiative
-
in fluid dynamics, turbulence modeling, CFD, and turbomachinery. Experience with CAD and CFD tools (e.g., Ansys Fluent, CFX, StarCCM+, OpenFOAM). Programming skills (e.g., Python, MATLAB). Knowledge
-
sustainable future through materials science. All early-stage researchers recruited into the WISE programme will be a part of the WISE Research School , an ambitious nationwide programme of seminars, courses
-
%) Complete coursework relevant to the PhD program Your profile Required qualifications MSc degree in Environmental Engineering, Chemical Engineering, Civil Engineering, Biotechnology, or a related field
-
analysis using AI. Solid knowledge of signal processing and machine learning. Proficiency in programming (e.g., MATLAB, Python, C/C++). Strong written and verbal communication skills in English. The
-
aluminium. The candidate will investigate various methods for symbolic regression, aiming to extract symbolic information, like mathematical functions or programs from a network trained for material modelling