PhD position on Sparse Training for Energy-Efficient Deep Learning

Job description

The main goals of this PhD project are:

• Develop novel sparse training algorithms that improve the scalability and energy efficiency of deep neural networks.
• Investigate the mathematical underpinnings of sparsity in deep learning and its effects on learning dynamics, and generalization.
• Implement and benchmark sparse training methods to scale up deep learning.
• Publish and present research findings in top-tier conferences (e.g., NeurIPS, ICLR, ICML, IJCAI, AAMAS, ECMLPKDD) and journals (e.g., Machine Learning, JMLR).
• Collaborate with an international team of researchers and industry partners.

The successful candidate will be embedded in the DMB research group, and the supervision will be ensured by Dr. Elena Mocanu and Prof.dr. Maurice van Keulen. This PhD position is part of the Modular Integrated Sustainable Datacenter (MISD) project and will have ample collaboration opportunities. As part of the MISD project effort led by Elena Mocanu, we are opening multiple positions (two Ph.D. candidates and one PostDoc) to join us and work at the interplay of dynamic sparse training in neural networks on various tasks.

Useful links:

• Elena Mocanu webpage
• DMB research group
• MISD project
• Sample of our work on sparsity

Your profile

• You are a scientific curiosity driven researcher;
• You have, or will shortly, acquire a master degree in the field of Computer Science, Mathematics, or a related field;
• You have excellent analytical, problem-solving, and communication skills.
• You have excellent coding and math skills (or the willingness and capacity to learn);
• You have the desire to conduct outstanding research and publish in high-quality Artificial Intelligence conferences and journals;
• You have a good team spirit and like to work in an interdisciplinary and internationally oriented environment.
• You are proficient in English

Our offer

• As a PhD candidate at UT, you will be appointed to a full-time position for four years, with a qualifier in the first year, within a very stimulating and exciting scientific environment;
• The University offers a dynamic ecosystem with enthusiastic colleagues;
• Your salary and associated conditions are in accordance with the collective labour agreement for Dutch universities (CAO-NU);
• You will receive a gross monthly salary ranging from € 2.770,- (first year) to € 3.539,- (fourth year);
• There are excellent benefits including a holiday allowance of 8% of the gross annual salary, an end-of-year bonus of 8.3%, and a solid pension scheme;
• The flexibility to work (partially) from home;
• A minimum of 232 leave hours in case of full-time employment based on a formal workweek of 38 hours. A full-time employment in practice means 40 hours a week, therefore resulting in 96 extra leave hours on an annual basis.
• Free access to sports facilities on campus
• A family-friendly institution that offers parental leave (both paid and unpaid);
• You will have a training programme as part of the Twente Graduate School where you and your supervisors will determine a plan for a suitable education and supervision;
• We encourage a high degree of responsibility and independence, while collaborating with close colleagues, researchers and other staff.

Information and application

Are you interested in this position? Please send your application via the 'Apply now' button below before 20 May 2024, and include:

• A brief motivation letter (maximum 2 pages), emphasizing (a) your individual reasons for desiring this role, (b) a reflective evaluation of your most and least developed skills (optional), and (c) your personal research interests and goals (optional).
• A full Curriculum Vitae, including your contact details, educational background, work experience (if any), publications (if any), and English proficiency test scores (optional).  
• Certified copies of degree certificates, with an accompanying detailed list of courses completed and corresponding grades.
• Names and contact details of 2-3 referees (they will be approached only if the candidate is shortlisted).

For more information regarding this position, you are welcome to contact Dr Elena Mocanu (e.mocanu@utwente.nl)

About the department

Our DMB collective stands by its diversity, inclusivity, and interdisciplinary composition. We are doing research at the forefront of advancements in machine learning, deep learning, and computer vision to advance scientific knowledge and societal welfare in a large spectrum of data science applications. We disseminate our research findings through publications in leading conferences (such as NeurIPS, ICLR, ICML, AAMAS, and CVPR) and prestigious journals (e.g. Nature Communications, Machine Learning, etc.).

About the organisation

The faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS) uses mathematics, electronics and computer technology to contribute to the development of Information and Communication Technology (ICT). With ICT present in almost every device and product we use nowadays, we embrace our role as contributors to a broad range of societal activities and as pioneers of tomorrow's digital society. As part of a people-first tech university that aims to shape society, individuals and connections, our faculty works together intensively with industrial partners and researchers in the Netherlands and abroad, and conducts extensive research for external commissioning parties and funders. Our research has a high profile both in the Netherlands and internationally. It has been accommodated in three multidisciplinary UT research institutes: Mesa+ Institute, TechMed Centre and Digital Society Institute.