The ELLIS PhD program has launched its second round of central recruitment and is accepting applications. A key element of the ELLIS initiative, the program's central aim is to foster and educate the best talent in machine learning and related research areas by pairing outstanding students from across the globe with leading researchers in Europe. The program also offers a variety of networking and training activities. Each PhD student is co-supervised by two ELLIS scientists based in different European countries. Over the course of their degree, students complete a mandatory exchange of at least six months at their co-advisor's lab. One of the advisors may also come from industry, in which case the student will collaborate closely with the private sector partner and spend their exchange conducting research at an industrial lab.
Research areas include (but are not limited to) the following machine learning-driven research fields: - Machine Learning Algorithms - Machine Learning Theory - Optimization - Deep Learning - Interactive and Online Learning - Reinforcement Learning and Control - Computer Vision - Computer Graphics - Robotics - Human Computer Interaction - Natural Language Processing - Causality - Interpretability and Fairness - Robust and Trustworthy Machine Learning - Quantum and Physics-based Machine Learning - Symbolic Machine Learning - Computational Neuroscience - Earth and Climate Sciences - Bioinformatics - Health
You can watch our introductory video here: https://www.youtube.com/watch?v=kWXNpnxkfg0.
The deadline for applications is November 15, 2021. Interested candidates should apply online through the ELLIS application portal. For more detailed information on the program, specific research areas, and the application process, please consult the call for applications: https://ellis.eu/news/ellis-phd-program-call-for-applications-deadline-november-15-2021 . -------------- next part -------------- A non-text attachment was scrubbed... Name: not available Type: text/html Size: 2618 bytes Desc: not available URL: <https://mailman.uib.no/public/corpora/attachments/20211027/41b2da29/attachment.txt>