Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
-
Field
-
deep learning, preferably including some exposure to graph neural networks or geometric deep learning. Proven experience with implementing machine learning methods in Python and Pytorch. Familiarity with
-
mathematics or related field Strong programming skills in python, C, C++ or other similar programming languages Strong communication skills in English, both oral and written The ability to work both
-
Engineering, Biomedical Engineering, Robotics, or related fields Strong programming skills (Python, MATLAB, and/or C++/C#) Knowledge of machine learning techniques, particularly for time-series data
-
) or a similar degree with an academic level equivalent to a two-year master's degree.[BN3] [SK4] Strong programming skills in Python and MATLAB Background in biomedical signal processing, ML, and BCIs
-
skills (e.g., Python, Java, or similar) Ability to work independently as well as in an international research team Excellent command of English, written and spoken. You must have a two-year master's degree
-
and applying new skills. Experience with programming in Python and a working knowledge of statistics It would further be beneficial if you have some of the following skills: Hands-on experience with
-
/scripting (e.g., Python, R, or Bash) Familiarity with next-generation sequencing data and genome assembly tools Strong analytical and problem-solving skills Excellent written and spoken English communication
-
SQUID magnetometry or similar techniques is a strong advantage. Experience in programming, ideally using Python to the extent that you can independently write programs to control and automate measurements
-
PhD scholarship in Runtime Multimodal Multiplayer Virtual Learning Environment (VLE) - DTU Construct
coding (e.g., Python, C#, C++) and demonstration in the development of serious games (e.g., Unity, Unreal) is required, ideally for pedagogical use Solid background or interest in emergency response
-
proficiency in relevant programming languages (e.g., Python, C++) and tools such as ROS. Experience in simulation and digital twins, as well as the use of synthetic data for training machine learning models, is