Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Employer
-
Field
-
with its grounding in cognitive theory. The position suits candidates with a PhD in Human-Computer Interaction or a related field who enjoy making empirical, methodological, and technical contributions
-
. This includes the use of Machine Learning (ML) and Artificial Intelligence (AI) methods. Project description The PhD project will be focused on developing, assessing, and comparing traditional and modern ML and
-
or related fields (with the degree obtained no longer than four years before the application deadline. Exceptions can be made with documented career breaks eg parental leave, illness, mandatory military/civil
-
dissemination is expected to focus on leading Human-Computer Interaction venues. For further information about the project, see: https://dff.dk/en/our-funded-projects/meet-the-researchers/research-leaders
-
organizational theory, the learning sciences, digital transformation, digital technologies, human-computer interaction, and related fields. Within the specific field, the PhD student will engage in both research
-
dissemination is expected to focus on leading Human-Computer Interaction venues. For further information about the project, see: https://dff.dk/en/our-funded-projects/meet-the-researchers/research-leaders
-
technologies Development and utilization of high throughput methods for characterizing and quantifying the physicochemical behavior of food macromolecules in complex matrices. Modelling and the use of machine
-
are at the core of anomaly detection and despite being a well-established field of research, these are still very much open problems. To this end, we are looking for candidates interested in developing new machine
-
studying how wireless sensing and AI interact in real systems. The work will be carried out in close collaboration with researchers in wireless communications, sensing, machine learning, and robotics, with
-
reduction, system identification, power electronics, model predictive control, multi-objective optimization, machine learning, renewable-energy integration, experimental testing, or hardware-in-the-loop