Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
-
Field
-
sequencing data and optimise editing conditions Execute pooled functional screens to identify synergistic gene combinations Validate hits with targeted assays and in‑vitro models Contribute to B.Sc./M.Sc
-
and what they mean for the system’s efficiency and safety. You will develop models of AI bidding strategies, analyze strategic interactions using game theory, and design optimization methods to identify
-
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
-
conversion reactions. The second position is focused on modelling stability of electrocatalyst materials. The aim is to develop a framework to predict metastability of catalyst materials. Among the methods
-
market frameworks and business models for fair value distribution will be analysed. Responsibilities and qualifications Your primary research tasks will include: Develop and simulate coordinated control
-
a team of 25 colleagues dealing with CCUS, and industrial partners in Denmark as well as abroad. Your primary tasks will be to: Apply AI in context of capture solvent modelling Understand and analyse
-
mathematical foundation of machine learning models. You will be responsible for developing scientific machine learning methodologies enabling new approaches for solving machine learning problems including
-
at the Niels Bohr Institute, Faculty of Science, University of Copenhagen. We are located in Copenhagen. We offer creative and stimulating working conditions in a dynamic and international research environment
-
competences within computational modelling, optimization and integration of thermal energy storage technologies – such as large water pits and phase change material storage. You will work with colleagues, and