Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Field
-
Junior Research Group “ Probabilistic Methods for Dynamic Communication Networks“ (Head: Prof. Dr. B. Jahnel) starting as soon as possible. The position is within the Math+ project "Information Flow
-
the Leibniz Junior Research Group “ Probabilistic Methods for Dynamic Communication Networks“ (Head: Prof. Dr. B. Jahnel) starting as soon as possible. The position is within the Math+ project "Information Flow
-
applications as PhD Student Position (f/m/d) (Ref. 25/11) in the Leibniz Junior Research Group “Probabilistic Methods for Dynamic Communication Networks“ (Head: Prof. Dr. B. Jahnel) starting as soon as possible
-
network automation, resource optimisation, or 5G/6G networks would be a plus. An interest in developing AI-driven solutions for real-time, adaptive network environments. Language skills Good proficiency in
-
Networks, and ICT Services & Applications. The SIGCOM research group, headed by Prof. Symeon CHATZINOTAS, carries out research activities in the telecommunication and networking systems, including NTNs and
-
Networks, and ICT Services & Applications. This industrial PhD position is part of the "Autonomous Systems for Land, Air and Space" (ATLAS) IPBG Programme co-funded by the FNR, SnT, and a consortium of
-
computational modelling to be used to design and re-engineer flower architecture. The RA's main focus will be on computational modelling of gene regulatory networks for predicting the mechanisms leading
-
collegial Department (29 faculty) that nucleates a larger interactive community (nearly 100 faculty). We support an exceptional Graduate Training Program, host two training grants, a robust weekly seminar
-
., Cell Metabolism, 2023; Leung et al., Science Translational Medicine, 2022; Seelbinder et al., Nature Communications, 2023). MBD is currently coordinating the EU-funded consortium MiCCrobioTAckle
-
computational modelling to be used to design and re-engineer flower architecture. The RA's main focus will be on computational modelling of gene regulatory networks for predicting the mechanisms leading