Sort by
Refine Your Search
-
Computer Science, ranging all the way from abstract mathematics and theoretical physics to high-performance numerical simulation algorithms. As a Senior Scientist in the “Quantum Information and Quantum Many-Body
-
or a closely related field. • You have experience in matrix algorithms, data compression, parallel computing, optimization of advanced applications on parallel and distributed systems
-
, virtual assistants, or AI-driven systems such as chatbots, recommender algorithms, or generative AI. The position focuses on how communicative processes are shaped by and shape these technologies
-
prospective doctoral project proposal (max. 3 pages, incl. 1 page time schedule) Degree certificates Contact details of people who could provide a letter of reference Via our job portal/ Apply now - button If
-
prospective doctoral project proposal (max. 3 pages, incl. 1 page time schedule) Degree certificates Contact details of people who could provide a letter of reference Via our job portal/ Apply now - button If
-
of subsequent permanent employment. Your future tasks: Operation and management: Oversee the daily operations of the NMR core facility, with responsibility for personnel, scheduling, and budget management. User
-
/ Diploma Interviews are scheduled to take place in mid-January 2026 Via our job portal/ Apply now - button If you have any questions, please contact: Manuela Ciotti manuela.ciotti@univie.ac.at We look
-
references) Doctoral degree (or confirmation that the PhD defense is scheduled; defense date must be before the start date of this position) Transcripts of record (BSc, MSc, PhD, if applicable) Contact details
-
if the employer does not terminate it within the first 12 months by submitting a non-extension declaration. The position is scheduled to be filled on March 1st 2026. Your future tasks: As a university assistant
-
: Parallel Computing Cloud Computing Performance Analysis and Optimization Communication Technologies for Supercomputers Workload Management and Scheduling Optimization of LLM Training and Inference Our