ELLIS Excellence Fellowship for Radboud Master Students
Students can now apply for the spring 2024 round!
Are you interested in fundamental, in depth machine learning research? Are you an excellent student who wants to take on an extra challenge? Are you interested in potentially pursuing an academic career and have the ambition to write an academic paper of high quality? Then this ELLIS excellence fellowship might be for you!
Here at the Nijmegen ELLIS unit, we have over 30 years of experience in fundamental, in depth machine learning research and education. Together we form one of the leading machine learning hubs in the Netherlands. The unit spans a vast breadth of research interests, and in particular:
- Machine learning and causal discovery, with applications in amongst others, healthcare, physics and the physical sciences, neuroscience, and industry driven applications
- Brain-inspired computing and development of statistical machine learning techniques with concrete applications in cutting edge neuroscience
- Understanding the computational aspects of machine learning using concepts and methods from theoretical physics and quantum machine learning
- Interpretable machine learning, Bayesian and information-theoretic inference methods for extremely high-dimensional data
- Deep and transfer learning for medical image analysis and kernel methods for Gaussian Processes to perform long-term forecasting
- Deep machine learning for medical image analysis and computer-aided diagnostics
- Multimedia analysis, including speech and language processing and computer vision; recommender systems; and information retrieval
- Robustness and dependability of machine learning in robotics and planning applications. (for this fellowship)
About the Fellowship:
This fellowship is suitable for you if you are interested in an academic career and have the ambition to write an academic paper of high quality. We expect the workload of this fellowship to be full-time for a duration of 6 months.
Our aim is to make these fellowships accessible to all our excellent students, and we want to try to make sure that all students get equal access. Therefore we are happy to announce that we are able to offer a fee of €500,- gross per month.
We furthermore would like you to join us every Wednesday at our Radboud AI/ELLIS location at the 20th floor of the Erasmus building, and ask for your support in organizing some events for the ELLIS unit.
When a student is selected they/she/he will receive (upon successful completion):
I. A certificate of participation with a pass or fail;
II. Two letters of recommendation: for the student that will help them in their continued (academic) career;
III. Access to the ELLIS network: we strongly encourage students accepted to this program to start and build a network of both good students and more importantly ELLIS unit members;
IV. €500,- per month, for the duration of the fellowship*.
Other desired outcomes outside of the appraisal criteria:
I. A clear understanding and sustainable code base for the project/notes/experiments etc.;
II.The research project should culminate in a master thesis, that potentially could be the start of a publishable paper in a respected top-tier journal or conference.
- Performing literature research and background survey: How much can a student understand the field they are in, and understand the scope of the problem they want to work on.
- Learning new ideas: How did the student adapt and learn new tools/methodologies/concepts.
- Coding and running/designing experiments: How is the student proficient in coding, how dominant were they designing the ML/DL experiments and how did they run them.
- Formulating research question: How pro-active and independent was the student in formulating the research question.
- Performing research: How was the student during the fellowship of research, how was their interaction with their adviser, how independent were they and how was the overall process of performing research.
- Writing of the paper: How was the student involved in the writing process and was the paper of sufficient quality of being published according to the supervisor.
If you have any questions, let us know! Send them to ELLISemail@example.com