Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
-
Field
-
and written) are required We offer • International, interdisciplinary working environment • In-house modelling, data processing and data assimilation expertise, software, and High Performance
-
an assessment of your education performed by the Ministry of Higher Education and Science 4. Publication list (if possible) The application, in English, must be submitted electronically by clicking APPLY NOW
-
, software, and High Performance Computation (HPC) infrastructure; • Excellent scientific infrastructure; • Participation in project meetings and international conferences; • Flexible working hours
-
At the Faculty of Engineering and Science, AAU Energy, a position as PhD stipend is available within the general study program. The stipend is open for appointment from 1. July 2026 or soon
-
DTU Tenure Track Researcher in Experimental High Pressure Phase Behavior for CO2 Storage and Othe...
to the development and improvement of experimental methods and measurement techniques in this field. High-pressure phase behavior and thermophysical properties are essential for the reliable design and safe operation
-
their own research project (under supervision). The programme culminates in the submission of a PhD thesis, which the student must defend in public. The programme is prescribed to 180 ECTS credits
-
researchers in our international and interdisciplinary program, MICROSUNSET brings together experts from several disciplines as supervisors, forming a consortium of seven beneficiaries (see above) and fourteen
-
around 200 research different aspects of photonics. Research is performed within nanophotonics, photonic nanotechnology, lasers, quantum photonics, optical sensors, LEDs, photovoltaics, ultra-high speed
-
combination of activities including securing competitive funding at national and European levels, building new collaborations within DTU and with external stakeholders, and initiating high-impact scientific
-
of this PhD project is to develop machine learning algorithms that perform efficiently and coherently across both classical and quantum computing platforms. The PhD project falls under the collaboration between