Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Employer
-
Field
-
for human control of complex robotic systems with high levels of agency and minimal cognitive effort. Short description: This project will develop novel AI algorithms to decode human intention from
-
create a closed loop pipeline able to rapidly design binders to any target and optimized for developability. The program is rooted in DALSA (DTU’s Arena for Life Science Automation), a new
-
research environment focusing on integrating multi-source data and developing novel algorithms to address the challenges posed by global environmental change. You will focus on integrating experiments, field
-
. Variational Autoencoders, Normalized Flows, Generative Adversarial Networks) Have experience in developing fast algorithms for hard combinatorial optimisation problems. Have some knowledge about stochastic
-
interface, and all the way to quantum algorithms and applications. The long-term mission of the programme is to develop fault-tolerant quantum computing hardware and quantum algorithms that solve life
-
initiatives towards the development of new environmentally friendly products, cleaner and more sustainable manufacturing and farming processes, new medical treatments, and richer biodiversity and ecosystems. In
-
better and faster decisions when assessing funding applications, ensuring the efficient and unbiased elimination of poor applications? This question can be addressed through training algorithms on past
-
(entities) given the rules and the rules given the molecules. The aim of this project is to develop a theory and accompanying algorithms to decide if an abstract system can be instantiated by a concrete
-
the loop and using active learning to determine which demonstrations to collect. The candidate would work on both projects and be responsible for: Implementing AI and probabilistic ML algorithms Development
-
electricity price signals, demand-response mechanisms, and time-of-use optimization. AI-Driven Optimization using Reinforcement Learning: Apply RL algorithms to develop and train agents that optimize power