18 project-manager-science PhD positions at Technical University of Denmark in Denmark
Sort by
Refine Your Search
-
tasks will be to: Genetic engineering of bacteria. Phenotypic characterisation of engineered strains. Teach and supervise BSc and MSc student projects. You must have a two-year master's degree (120 ECTS
-
DTU Management’s Management Science division. The project is led by Professors Stefan Ropke and Richard Lusby and involves international collaboration with leading researchers in machine learning and
-
development and marine management. Your primary tasks will be to: Compile and harmonize data from multiple sources (e.g., EMODnet, Copernicus, fisheries surveys, citizen science). Engage with data managers and
-
you will break new ground at the absolute forefront of what is possible in safe operation of autonomous agricultural vehicles. These are needed to enable better land use and management. This project
-
, might be for you! Responsibilities and qualifications Working with colleagues in the MULTIBIOMINE project, you will develop computational methods that use novel strategies to uncover hidden features in
-
research environment. Project background Future European power systems are expected to be driven by a very high share of renewable power plants and will be extremely complex, uncertain environments with
-
foods for the future? If you have knowledge within the area of allergy and protein-chemistry as well as have hands-on experience with cell-based in vitro models and are looking for a PhD fellowship
-
power. Your primary tasks will be to: Develop a detailed 3D multiphysics model of the HT-PEMFC stack to analyze and optimize thermal management. Design a heat recovery system, tailored
-
for effective tool wear management. This position offers unique opportunities with respect to high level research, training and innovation within manufacturing engineering, in an exciting combination of academic
-
, data science, computer science, and computer engineering, including artificial intelligence (AI), machine learning, internet of things (IoT), chip design, cybersecurity, human-computer interaction