The Informatics Institute of the Faculty of Science invites applications for a PhD candidate in Efficient Deep Learning for four years. The position is  part of the Dutch STW Efficient Deep Learning program. 

The EDL program combines the fields of machine learning and computing: both disciplines are already strong in the Netherlands and now connected by seven Dutch academic institutes and more than 35 other (industrial) partners in- and outside the Netherlands. The EDL program contains seven use case driven EDL research projects: P1) DL as a service, P2) Reconstruction, matching and recognition, P3) Video analyses and surveillance, P4) High tech systems and materials, P5) Human and animal health, P6) Mobile robotics, and P7) DL platforms. The common goal for all seven EDL projects is to significantly improve the applicability of DL among others by creating data efficient training, and tremendously improving computational efficiency, both for training and inference.

Partners in EDL-P4 are the Dutch universities TU/e, UvA and VU, and also Thermo Fischer, Qualcomm (Scyfer), the Netherlands eScience center, ASTRON and SURFsara.

The PhD candidate will work on DL for extreme-scale system health management. The candidate will work on the development of energy and resource efficient DL algorithms. She or he will work on implementations to accelerate DL by programmable hardware (e.g. GPUs).

Tasks:

• conduct interdisciplinary research with a special focus on the design and implementation of novel scalable DL algorithms that deal with extremely large, heterogeneous and sparse data in real time;
• investigate novel architectures for real-time efficiency and power efficiency at exascale;
• implement and validate DL-based SHM in radio telescopes;
• publish in top tier conferences and journals in relevant areas;
• provide teaching assistance (10%);
• complete a PhD thesis.

The PhD candidate will work at the Systems and Networking lab of the Informatics Institute at the University of Amsterdam and at ASTRON (Dwingeloo). Regular travelling between the two sites is expected.

We are looking for candidates whose skills match with (a large part of) the following profile:

• an MSc. in Computer Science, AI or related disciplines with excellent grades;
• demonstratable experience with High-Performance Computing (parallel programming, networking, GPUs);
• affinity with Signal Processing, Machine Learning (ideally deep learning), and a good mathematical background are important;
• excellent programming skills (in C, C++, Python);
• a team player who enjoys a multicultural and interdisciplinary environment in which academic-industrial collaboration is central;
• good communication and organization skills;
• excellent English language skills (writing and presenting).

The appointment will be full-time (38 hours a week) for a period of four years (initial employment is 18 months). Periodic evaluations will be held after 9 and 14 months. Upon positive evaluation, the appointment will be extended to a total of 48 months. The appointment must lead to a dissertation (PhD thesis). An educational plan that includes attendance of courses, summer and/or winter schools, and national and international meetings will be drafted for the PhD candidate. The PhD candidate is also expected to assist in teaching of undergraduate students.

The salary is in accordance with the university regulations for academic personnel. The salary will range from €2,266 (first year) up to a maximum of €2,897 (last year) before tax per month (scale P) based on a full-time appointment. There are also secondary benefits, such as 8% holiday allowance per year and the end of year allowance of 8.3%. The Collective Labour Agreement for Dutch Universities is applicable.

Among other things, we offer:

• competitive pay and excellent benefits;
• extremely friendly working environment;
• high-level of interaction;
• international environment (10+ nationalities in the group);
• access to high-end computing facilities (cluster with 4,000+ cores);
• one of the best AI ecosystems on the planet;
• new building located near the city center (10 minutes by bicycle) of one of Europe’s most beautiful and lively cities;
• access to one of the largest radio telescopes in the world (LOFAR) in a beautiful environment (a national park).

Since Amsterdam is a very international city where almost everybody speaks and understands English, candidates need not be afraid of the language barrier.

University of Amsterdam

With over 5,000 employees, 30,000 students and a budget of more than 600 million euros, the University of Amsterdam (UvA) is an intellectual hub within the Netherlands. Teaching and research at the UvA are conducted within seven faculties: Humanities, Social and Behavioural Sciences, Economics and Business, Law, Science, Medicine and Dentistry. Housed on four city campuses in or near the heart of Amsterdam, where disciplines come together and interact, the faculties have close links with thousands of researchers and hundreds of institutions at home and abroad.  

The UvA’s students and employees are independent thinkers, competent rebels who dare to question dogmas and aren’t satisfied with easy answers and standard solutions. To work at the UvA is to work in an independent, creative, innovative and international climate characterised by an open atmosphere and a genuine engagement with the city of Amsterdam and society.

http://www.uva.nl/en/home

Systems and Networking Lab

The Systems and Networking (SNE) lab is a research lab at the Informatics Institute of the University of Amsterdam. The Systems and Networking lab conducts  research on leading-edge computer systems of all scales, ranging from global-scale systems and networks to embedded devices.

Across these multiple scales our particular interest is on extra-functional properties of systems, such as performance, programmability, productivity, security, trust, sustainability and, last but not least, the societal impact of emerging systems-related technologies.

Our approach to research is a practical and engineering-oriented one that regularly involves the design, implementation and maintenance of prototypical tools and proof-of-concept applications that demonstrate and promote our research results.

https://ivi.fnwi.uva.nl/sne/