63 brain-computer-interface PhD positions at Technical University of Denmark in Denmark
Sort by
Refine Your Search
-
), robotics and computing, construction production processes, and life cycle and sustainability analysis (LCA). The successful candidate will be responsible for conducting cutting-edge research in the field
-
with the Danish Confederation of Professional Associations. The allowance will be agreed upon with the relevant union. The position is part of DTU’s Tenure Track program. Read more about the program and
-
The project involve conducting high-quality research at the intersection of thermo-fluids science, AI/machine learning and optimization. We envision that: You have an open mind and can think creatively in
-
on turning exiting challenges into solutions based on curiosity and an open mind for entering new paths when necessary. You have a natural flair for driving things forward on you own, and you like to create
-
forefront of protein science and biophysics—tackling the molecular origins of neurodegenerative diseases of the brain. The overall aim of the research is to achieve a deep understanding of how protein
-
international research portfolio. Experience with sustainable protein production, especially at the interface of protein and material sciences, including designing and expressing functional proteins for novel
-
“Bioactives – Analysis and Application”. As part of this prestigious Alliance PhD program, you will collaborate closely with Queensland University in Australia and the University of Copenhagen in Denmark
-
international PhD researchers, gaining access to dedicated training events, coding bootcamps, hackathons, and transferable skills workshops as part of the MSCA Doctoral Network programme. Based at DTU Wind’s
-
processes, preferably HTPEM fuel cells. Proficiency in relevant computational tools, such as COMSOL Multiphysics. Familiarity with degradation mechanisms and the transient behavior of PEM fuel cell stacks is
-
in machine learning and artificial intelligence Experience with numerical analysis and scientific computing Knowledge of power systems and renewable energy technologies Experience in power system