Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
-
Field
-
biomedical engineering. We currently host several Ph.D. and postdoctoral fellows from Denmark and multiple nationalities. The group’s research interest spams from musculoskeletal simulations to design and
-
machine learning for safe and optimal control of cyber-physical systems. The projects are expected to be funded by the VILLUM INVESTIGATOR project S4OS (“Scalable analysis and synthesis of safe, secure and
-
on developing machine learning algorithms to support the use of complex urban simulators in decision-making under uncertainty. This PhD project shifts the focus from optimality to relevance in urban land-use and
-
objective is to surpass the current traditional thermodynamic and optimization approaches, which are constrained in design discovery capabilities and long-term TES performance evaluation. Through your
-
on generating new knowledge for optimizing biological conversion of carbon dioxide to acetic acid in close collaboration with an industrial end-user of the developed technology. Responsibilities and tasks Your
-
the ambitions to accelerate the detection and optimization of sustainable chemical approaches through the development of novel reactions and advanced analytics using state of the art high-field and hyperpolarized
-
renewable power system dynamics. Collaborate with experts from DTU and IIT Bombay, gain hands-on experience with advanced simulation tools, and contribute to high-impact publications. Enhance your
-
of Campylobacter through literature review and conduct interviews to assess the current biocide use in the Danish poultry industry. Develop, optimize, and validate culture-independent assays by planning and
-
the optimization of bioactive compound extraction from various seaweeds for the development of fortified foods. This PhD position aims to (i ) identify suitable seaweed species for high-yield protein extraction, (ii
-
academic partners in Europe and globally. Candidates with the following qualifications will be preferred: Educational background in power systems. Documented knowledge in optimization in power and energy