Sort by
Refine Your Search
-
PhD scholarship in Runtime Multimodal Multiplayer Virtual Learning Environment (VLE) - DTU Construct
the furthermore, core works are envisioned in (c) initiating novel VLE design using foundational Digital Twin for Construction Safey (DTCS) components (e.g., city models, nD BIM, IoT/sensor data, TPTC, LPS, LBS
-
material characterization, material flow analysis and material recycling. This PhD opportunity is part of the Marie Skłodowska-Curie Doctoral Network SCARPA , a European training network committed
-
working with live animals. Excellent skills for data handling and statistical analysis. Strong written and oral communication skills in English. Ability to work both independently and as a part of a team
-
your chance to shape the future of smart food regulation, both in Denmark and globally. At DTU Food, you'll be part of an ambitious research team that is redefining regulatory food systems in Denmark's
-
energy modeling and analysis to be part of the Ports as Energy Transition Hubs (POTENT) Marie Sklodowska-Curie Actions Doctoral Network. The network will consist of 15 PhD candidates interested in
-
complete picture of fish habitat use and connectivity. The PhD is part of the section for Ecosystem based Marine Management and the Marine Habitats research group, as well as several synergistic initiatives
-
. These tools will be integrated with physics-based models of environmental loading (waves and wind) to enhance the accuracy and robustness of the assessment. All components assembled together will finally inform
-
where variable renewable energy sources are involved. Emerging digital and cyber-physical systems technologies are an integral component of grid interactive efficient buildings. Through advanced control
-
international conferences, is an integral part of the job. You must have a two-year master's degree (120 ECTS points) or a similar degree with an academic level equivalent to a two-year master's degree in
-
for Science & Technology (KAIST), and an external stay at KAIST will be included as part of the PhD program. Qualifications Proficiency with Python Experience implementing various Machine Learning algorithms