Sort by
Refine Your Search
-
development, employing machine learning techniques applied to industrial datasets, and in collaboration with industry. The applicant will work in the Software Engineering Theme, which is one of several Themes
-
., topological data analysis and machine learning. We welcome applications from all qualified candidates regardless of personal background. Further information on the Department can be found at https://di.ku.dk
-
Research, University of Copenhagen, Denmark. Candidates should have a strong background in (genetic) epidemiology, bioinformatics, statistical genetics, data science, machine learning, or a closely related
-
methods for assessing generative AI’s compliance to GDPR. The purpose of the position is to build Bayesian metrics for privacy preserving AI(e.g., synthetic data generation, federated learning, and privacy
-
/mechanical engineering, computer graphics/vision, machine learning, or other related skills that are useful for fabricating new types of physical objects and interfaces excellent programming skills Your
-
is founded by Innovation Found Denmark. Responsibilities: In the project two main approaches are compared. One based on black/gray box machine learning methods and another one on gray/white box data
-
well familiar with machine learning algorithms both theoretically and practically in implementing them You are proficient communication skills You have excellent English skills written and spoken You
-
background and the group at www.healthtech.dtu.dk/Isoform-Analysis Responsibilities Your objective will be to use probabilistic modeling and machine learning to create bioinformatic tools and databases
-
opportunity to learn new analysis techniques(e.g., Matlab, Python) if relevant for the task. Write up research results in the form of journal articles. Participate in and co-arrange national and international
-
). Training will be provided in all methodologies but prior experience with some techniques is an advantage, and experience in human pain research is a prerequisite. An opportunity to learn new analysis