Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Employer
-
Field
-
stability. Affinity with numerical simulation, algorithm development and scientific programming. Excellent communication skills in English. The following are considered assets: Knowledge of power electronics
-
advanced planning and control algorithms, real-time and energy-efficient sensing, and distributed perception. Its research is applied across diverse sectors, including agriculture, manufacturing and remote
-
to translate fundamental discoveries into sustainable agricultural applications and to enhance the climate resilience of crops. This PhD position will be embedded in the Bioinformatics and Evolutionary Genomics
-
algorithms capable of operating in large, partially observed spatial domains to infer efficient, interpretable strategies for estimating archaeological potential, that capture distinct criteria including
-
layers. Within this environment, we will design and evaluate new reinforcement learning algorithms capable of operating in large, partially observed spatial domains to infer efficient, interpretable
-
, operational, and societal constraints. The postdoc will work at the interface of reinforcement learning and computational epidemiology, focusing on the development of new reinforcement learning algorithms
-
of trustworthy neurosymbolic AI. There is both a theoretic and practical component to this topic, since the ultimate goal is to implement efficient algorithms that allow reasoning engines to produce
-
Group Leader and Professor AI in Biology - Dept of Computer Science and Dept. Electrical Engineering
and numerical algorithms from linear algebra, statistics, optimization, machine learning, and AI, applying them to advance technology in fields like industrial automation, speech processing, digital
-
of underlying 3D scene representations. This requires the designing and developing of specialized computer-generated hologram (CGH) algorithms, modeling the propagation of incoherent light through space
-
simultaneously provide reliable wireless connectivity and high-precision sensing. The objective is to develop localisation and sensing algorithms that achieve near-GNSS accuracy while improving robustness, energy