Sort by
Refine Your Search
-
relevant research experience. The ability to disseminate research results through academic publications and scientific events is essential for the position. A high level of computer literacy is required, and
-
incapacity for work (if the doctoral degree was obtained more than 7 years before the application deadline). Other documents proving scientific competence. Document submission procedure: • Documents must be
-
a group of researchers conducting research in business management (strategic management or human resource management, or project and process management). They will teach students management (business
-
. 40 working days of holidays per year. Selection process Applicants will be assessed according to: DORA principles, emphasising qualitative research contribution over quantitative indicators
-
) projects in healthy ageing, public health, gerontology, or life-course health, integrating biomedical, behavioral, social, and technological approaches. Knowledge of ageing processes and determinants
-
to growing as research leaders. APPLICATION PROCEDURE Applications must be submitted by email to cv@mruni.eu no later than 22 February 2026. Applicants must submit the following documents: a Narrative (skills
-
to innovation valorization processes and organizational collaboration models. Act in accordance with the Center's internal rules, perform the duties defined in the official CoE documents, and comply with
-
, multimodal data processing, computer vision, NLP, or digital twinning. Experience with AI applications in health, transport, energy, or manufacturing is an advantage. Strong understanding of responsible AI
-
Development HUB will: Oversee HR-related processes, including recruitment, staff development, performance management, and mobility. Coordinate administrative and financial operations of the CoE. Manage legal
-
perfusion, which can be reflected in these signals. The research aims to identify biosignal-derived markers associated with acid–base regulatory mechanisms and to develop physiology-informed signal processing