This program is meant for doctoral candidates whose research interests are well matched to both the machine learning group in Cambridge (United Kingdom) and the MPI for Intelligent Systems in Tuebingen (Germany).
The University of Cambridge Machine Learning Group and the Department of the Empirical Inference at the Max Planck Institute for Intelligent Systems in Tübingen are two of the world’s leading centres for machine learning research. In 2014, we launched a new and exciting initiative whereby a small group of select PhD candidates are jointly supervised at both institutions.
The principal supervisors are Zoubin Ghahramani, Carl Rasmussen, Richard Turner, Jose Miguel Hernandez-Lobato and Adrian Weller at Cambridge University, and Bernhard Schoelkopf and other research group leaders at the Max Planck Institute in Tübingen. This is a unique programme, and admission in the last years was highly competitive. We encourage applications from outstanding candidates with academic backgrounds in Mathematics, Physics, Computer Science, Engineering and related fields, and a keen interest in doing basic research in machine learning and its scientific applications. There are no additional restrictions on the topic of the PhD but for further information on our current research areas please consult our webpages at Department of Computational and Biological Learning at the University of Cambridge and Department of Empirical Inference at the Max Planck Institute for Intelligent Systems, Tübingen.
The overall duration of the PhD will be four years, with roughly three years spent at one location, and one year spent at the other location, including initial coursework at the University of Cambridge. Successful PhDs will be officially granted by the University of Cambridge. We plan to offer funding for up to two PhD Fellowships covering university tuition fees (at Cambridge EU rates) and a stipend of approximately 17000 Euros (about 14500 GBP) per year. We acknowledge generous financial support from Microsoft, Facebook and Amazon.
Applications to the Cambridge – Tübingen PhD Fellowships should be made by first applying to the Cambridge PhD programme in Advanced Machine Learning as described here. Once you have completed the application to the Cambridge PhD Programme, and before actually submitting it, you should download the application and send a copy to camtue@is.mpg.de. It is important to download the application before its submission to the GRADSAF system at the University of Cambridge because the application is no longer available once it is submitted. Please use the subject line “Cambridge-Tuebingen PhD fellowship” in your email to camtue@is.mpg.de.
Furthermore, applications for Tübingen should include a CV, a short mission statement and scanned transcripts. Please arrange for 2-3 reference letters to be sent directly to camtue@is.mpg.de.
Any questions regarding academic suitability should go to Miguel Hernandez-Lobato. Please use the subject line "Cambridge-Tuebingen PhD fellowship".
Applicants must formally apply through the University of Cambridge webpage), indicating the Department of Engineering as the host department (course: “PhD in Engineering (probationary)”, supervisors: Zoubin Ghahramani, Carl Rasmussen, Richard Turner, Miguel Hernandez-Lobato).
Applicants should also make sure that they apply for “Cambridge Trusts”, “Gates Cambridge”, and “Other Research Councils” funding by ticking the relevant boxes in the application form
(see http://www.graduate.study.cam.ac.uk/application-funding-deadlines for details).
The hard deadline for formal applications is October 29, 2018.
Interviews will take place in Tübingen on January 14-16, 2019.
We look forward to receiving your applications.
machine learning
empirical inference