Sort by
Refine Your Search
-
Wiberg is “Innovative statistical and machine learning methods for comparing performance and outcome in register data studies”, with overall aim to develop, evaluate, and implement innovative statistical
-
multimodal machine learning. Admission requirements The general admission requirements for doctoral studies are a second- cycle level degree, or completed course requirements of at least 240 ECTS credits
-
humans and society at large is either fully automated or heavily relies on automatically provided decision support. While machine learning approaches become increasingly prevalent in this context
-
Galileo missions and the Hubble Space Telescope. This project uses computer simulations to study plume-plasma interactions and compares results with spacecraft data. The project leader is Associate
-
education to enable regions to expand quickly and sustainably. In fact, the future is made here. Are you interested in learning more? Read about Umeå university as a workplace Description of work About the
-
presents a unique opportunity to join a cohort of other doctoral researchers in the research school and learn alongside each other in carefully designed courses that align with the excellence centre’s
-
with different backgrounds and perspectives lay the foundation for learning, creativity and development. We welcome people with different backgrounds and experiences to apply for the current employment
-
deadlines, personal suitability. Very good spoken and written English skills are required. Knowledge of both spoken and written Swedish or willingness to learn Swedish within two years from the start of
-
and eagerness to learn the required techniques as well as interest in the meritorious skills and experiences. On a personal level, we are looking for a good team player who can also work on their own
-
for protein structure and function determination (e.g., X-ray crystallography, NMR, cryo-electron microscopy). You will learn how to use advanced bacterial culture conditions to grow the species of the human