The University of Cambridge Machine Learning Group and the Max Planck Institute for Intelligent Systems Empirical Inference Department 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, Neil Lawrence, 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 http://mlg.eng.cam.ac.uk and http://ei.is.tuebingen.mpg.de.
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.
Applicants from Europe don’t need an employment visa, for those who apply from non-EU countries it is necessary to inform themselves at the embassy of their country about visa procedures.
We appreciate that Brexit leads to increased uncertainty when it comes to studying in the UK. Comprehensive information regarding issues surrounding Brexit, such as immigration, fees, and travel, is available on https://www.eu.admin.cam.ac.uk and updated frequently. In particular, we would like to reassure prospective Cambridge-Tuebingen students that appropriate funding will be available to cover living expenses both in Cambridge and in Tuebingen.
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.
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.
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 email@example.com. It is important to download the application before submitting it through the academic portal because the application is no longer available once it is submitted. Please use the subject line “Cambridge-Tuebingen PhD fellowship” in your email to firstname.lastname@example.org. Please arrange for a cv, a motivation letter, BSc. and MSc. transcripts, and two reference letters of your application to the Cambridge PhD programme in Advanced Machine Learning to be sent also to email@example.com.
The hard deadline for formal applications is November 3, 2019.
Interviews will take place in Tübingen from January 13, 2020 until January 16, 2020.
The Max-Planck Society is committed to increasing the number of individuals with disabilities in its workforce and therefore encourages applications from such qualified individuals. Furthermore, the Max Planck Society seeks to increase the number of women in those areas where they are underrepresented and therefore explicitly encourages women to apply.
The University of Cambridge is commited in its pursuit of academic excellence to equality of opportunity and to a proactive and inclusive approach to equality, which supports and encourages all under-represented groups, promotes an inclusive culture, and values diversity.
We look forward to receiving your applications.
Zoubin Ghahramani Bernhard Schölkopf
University of Cambridge Max Planck Institute for Intelligent Systems