Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Employer
-
Field
-
About the SnT The University of Luxembourg is an international research university with a distinctly multilingual and interdisciplinary character. The Interdisciplinary Centre for Security, Reliability and Trust (SnT) at the University of Luxembourg is a leading international research and...
-
are dynamic systems evolving over time (due to operation), this doesn’t hold. Therefore, there is much to be gained by surrogating the full structure flexibly: a generalist surrogate capable of estimating and
-
-savvy modelers, computer scientists and AI experts at VIB. Key Responsibilities Provide expert scientific and strategic guidance to early discovery programs across VIB, supporting small molecule
-
many real-world applications, finding a solution requires high-performance computer clusters that consume large amounts of energy and run for a long time. Our project aims to create a radically new
-
. For more information, please visit our website: www.uni.lu/snt-en/research-groups/finatrax/ The selected candidate will be enrolled in the PhD program in Computer Science and Computer Engineering with
-
identification and payments in a single app Advise Luxembourg's Ministry for Digitalisation on related activitiesPublish in top outlets on information systems, tech policy, and computer scienceSupport research
-
-of-the-art in SLAM, situational awareness, computer vision, machine learning, robotics, and related fields Developing and implementing innovative solutions, validated through real datasets and experiments
-
. The courses you will teach may include bachelor-level courses, such as Computer Networks, Distributed Systems, Computer and Network Security, Operating Systems, and master-level courses, such as Topics in
-
and Computer Engineering with specialization in Information Systems, which will allow a broad spectrum of interdisciplinary research. In particular, the successful candidate will be part of the E
-
the controlled flow at tunable temperature and photopolymerization of the precursor. The practical work will be complemented by fluid mechanics computer simulations, including solutions employing machine learning