12 machine-learning "https:" "https:" "https:" "https:" "The Open University" "The Open University" Fellowship research jobs at NTNU Norwegian University of Science and Technology
Sort by
Refine Your Search
-
where AI systems are reshaping how we learn, work and participate in democracy, our centre tackles the promise and peril of hybrid intelligence—human and machine working and learning together. AI LEARN’s
-
viability data to discover new biomarkers and treatment strategies. You will work in a highly interdisciplinary environment spanning oncology, cell biology, imaging, bioinformatics and machine learning, with
-
acquire such competence during the employment period. In such cases, you will also be assigned relevant teaching as part of the career-promoting work. The appointment is to be made in accordance with NTNUs
-
Norwegian courses. Required selection criteria You must have completed a doctoral degree in (machine learning, statistics, or similar). You must have a professionally relevant background in algorithms
-
professor in Norway, NTNU will arrange for you to acquire such competence during the employment period. In such cases, you will also be assigned relevant teaching as part of the career-promoting work
-
already have educational competence that meets the requirements for a position as associate professor in Norway, NTNU will arrange for you to acquire such competence during the employment period. In such
-
where AI systems are reshaping how we learn, work and participate in democracy, our centre tackles the promise and peril of hybrid intelligence—human and machine working and learning together. AI LEARN’s
-
will focus on the work package 'Learning, economic policy and business strategy in neutral countries'. During the First World War, the economies and companies of neutral countries adjacent to the Central
-
professor in Norway, NTNU will arrange for you to acquire such competence during the employment period. In such cases, you will also be assigned relevant teaching as part of the career-promoting work
-
Experience with visualisation methods Experience publishing interdisciplinary or applied research Experience designing or delivering courses, workshops, or studio-based learning Good oral and written