Sort by
Refine Your Search
-
application! We are looking for a PhD student in Environmental Science for research on Greenhouse Gases and Biodiversity in Agricultural Landscapes using Drone and Satellite measurements. Your work assignments
-
salary progression. The starting salary is 35 300 SEK per month before tax. The salary then increases after completing 30 %, and 60% of the PhD degree program, respectively. As an employee of Linköping
-
month before tax. The salary then increases after completing 30 %, and 60% of the PhD degree program, respectively. As an employee of Linköping University, you are entitled to the following benefits: Paid
-
application! We are looking for a PhD student in automatic control at the Department of Electrical Engineering (ISY). Your work assignments You will work on a project on data driven control. In recent years
-
duties, up to a maximum of 20 per cent of full-time. Your qualifications To be employed as a PhD student you need to have completed a degree at Master’s level in Electrical Engineering, Computer
-
application! Your work assignments Spatio-temporal processes are everywhere in science and engineering, with applications ranging from weather prediction to cardiovascular medicine. Developing machine learning
-
at Master’s level in Computer Science, Electrical Engineering, or Applied Mathe- matics with a minimum of 240 credits, at least 60 of which must be in advanced courses in Computer Science, Electrical
-
application! We are announcing a PhD student position in Computer Science within CUGS Research School in a joint effort with Cybercampus Sweden , formally based at the division for Cybersecurity at Department
-
economics and management to technology and design. The department is characterized by a strong focus on renewal, development, and innovation as means to contribute to a sustainable society. Many PhD graduates
-
application! We are looking for a PhD student in biomedical engineering with a focus on deep learning for medical images Your work assignments The position focuses on developing methods for federated learning