Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
-
Field
-
participate in an international team in an EU-funded Doctoral Network project called SiCPIC. The project consists of 15 PhD students at 5 universities and one company. The project has partners from five
-
classical communication networks to support both traditional data and the unique requirements of quantum information systems (https://www.classique.aau.dk ). CLASSIQUE will address a suite of fresh research
-
, CLASSIQUE focuses on a critical challenge: how to evolve classical communication networks to support both traditional data and the unique requirements of quantum information systems (https
-
scientists and has a large international network of collaborators. We seek committed candidates that can work focused and independently but that flourish in an international team having a strong, synergetic
-
on holistic understanding from regional net-zero. The PhD project is part of the Regional Energy, Carbon and Land Management initiative, focusing on optimizing energy infrastructure, land use and carbon flows
-
Candidate (DC), commencing 1 September 2026 or as soon as possible hereafter. The position is a full‑time appointment for 36 months and is funded by Horizon Europe. Interdisciplinary Network for Training
-
well as infection-trials in rainbow trout and possibly other fish species. Through our broad network of international collaborators, you will have ample opportunity for long and short research stays at scientific
-
climate adaptation measures. Emphasis will be placed on robustness and scalability of the modeling approaches. You will be part of a large global expert network under the IEA EBC Annex 96 - Grid Integrated
-
experiments Desirable: • Backend development (Python, Ruby, …) • Linux system administration (deployment, networking) • Experience with decentralized/self-hosted services, e.g. Mastodon, Nextcloud, Matrix
-
, or computational modelling, and you should be comfortable working with large datasets and modern deep learning frameworks. Experience with neural network design, optimisation techniques, or scalable computing is an