Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Field
-
Your profile PhD applicants must possess a Master's degree in mathematics, theoretical physics, or computer science. Candidates should have an exceptional academic record and a robust mathematical foundation. Candidates are also expected to have strong coding and implementation skills, with the...
-
the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description The research groups of Prof. I. Bogunovic and
-
and MIT (USA) as part of the project. Funding package: UK tuition fees (fully covered) Tax-free stipend of £18,423 p.a. Support for training, equipment, and travel Supervisors: Prof. Zengbo Wang (School
-
Disse), the Chair of Geoinformatics (Prof. Thomas H. Kolbe), and the Chair of Algorithmic Machine Learning & Explainable AI (Prof. Stefan Bauer). The project aims to develop an integrated urban flood
-
machine learning approaches. These are similar to earlier work on charge and excitation energy transfer (see https://constructor.university/comp_phys). The project for the PhD fellowship is slightly more
-
environment with excellent infrastructure. The candidate will benefit from joint supervision by Prof. Olga Fink (EPFL IMOS) and the UESL team at Empa, combining cutting-edge expertise in machine learning and
-
Primary supervisor - Prof Larissa Samuelson We invite applications to an exciting opportunity for fully-funded a PhD studentship working on a cutting-edge project examining early word learning and
-
assessment instruments are combined to gain a differentiated insight into family influence processes. The project is led by Prof. Dr. Anna Kornadt (Uni Luxembourg), Prof. Dr. Michaela Riediger and Dr. Antje
-
). Willingness to learn is expected, and the project provides ample of opportunities for acquiring novel skills and interdisciplinary perspectives. The ability to work in a diverse, multi-national team is required
-
You work at the Wenckebach Institute for Education and Training (WIOO) of the UMCG, within the Lifelong Learning, Education and Assessment Research Network (LEARN). The UMCG is the largest employer