Sort by
Refine Your Search
-
Listed
-
Employer
-
Field
-
degree (see notes below) in Computer Science, Applied Mathematics, Data Science, Computational Statistics, Bioinformatics, Computer Engineering, or related field that provides a sufficient background in
-
strong interest in aluminum alloys, fatigue analysis, and numerical modelling is preferred. Experience with computer aided design and engineering (CAE, e.g., Abaqus, Ansys) software tools commonly used in
-
Kontogianni. Our research explores how intelligent systems can perceive, understand, and interact with the 3D world. We develop new methods in computer vision, machine learning, and multimodal 3D
-
paradigms and assumptions. Thus, the research project is in the field of econometrics with focus on theory and methodology. The research questions can include, but are not limited to, research on estimation
-
Position in XAI with Commonsense Knowledge for Robotics and Computer Vision 2. PhD Position in Sustainable AI for Enhancing Health Informatics (Please scroll down to read more about the project descriptions
-
doctoral candidate who meets the following requirements: A background and strong interest in aluminum alloys, fatigue analysis, and numerical modelling is preferred. Experience with computer aided design and
-
environment with over 400 employees and 10 research sections. We broadly cover digital technologies within mathematics, data science, computer science, and computer engineering, including artificial
-
environment with over 400 employees and 10 research sections. We broadly cover digital technologies within mathematics, data science, computer science, and computer engineering, including artificial
-
sections. We broadly cover digital technologies within mathematics, data science, computer science, and computer engineering, including artificial intelligence (AI), machine learning, internet of things (IoT
-
theory-based estimates for the effects of government subsidies on household wealth and risks. Delivering evidence-based recommendations on the optimal subsidy regime. Main supervisor Professor Trine Krogh