PhD Position in Probabilistic and Differential Algorithms

Are you eager to jump-start your career in Differential and Probabilistic Programming? As a PhD candidate in the ERC project FoRECAST, you’ll work independently and in a collaborative, diverse team. This is a unique opportunity to contribute to the foundations for tomorrow’s machine learning.

Your job
In the ERC project FoRECAST, we aim to develop theory (e.g., new probabilistic and differential inference algorithms as well as proofs of their correctness and efficiency) and systems (e.g., high performance, functional array programming DSLs) to tackle challenging probabilistic and differentiable programming applications (e.g., experimental design, machine learning for science). We do so by bringing together a diverse team of PhD candidates who will focus on three key areas:

1. Probabilistic and differentiable algorithms for machine learning;
2. Programming language implementation for high performance computing;
3. Programming language semantics and foundations.

Your focus will be on area 1, and your research should lead to a PhD degree during your appointment.

Your research
In this role, your research will develop the foundations and push the boundaries of the field of differential and probabilistic programming. This exciting new field of research combines knowledge from the machine learning, programming languages, scientific computing, and statistical physics communities. Depending on your background and interests, your project could involve:

• developing new differential and probabilistic programming techniques (e.g., techniques for differentiating effectful programs such as gradient estimation of probabilistic programs, implicit function differentiation, compositional Bayesian inference techniques);
• giving mathematical proofs of their correctness and efficiency;
• building state-of-the-art implementations of these new techniques (e.g., by leveraging data-parallel functional array programming techniques);
• applying them to solve real-world problems (e.g., gradient estimation challenges in experimental design and reinforcement learning).

You’ll have plenty of space to shape the project to your particular interests and strengths.

Your team
Your main supervisor will be Matthijs Vákár. You’ll also be supported by secondary supervisors who are experts in machine learning, chosen to match your profile. Beyond membership of the FoRECAST team, you’ll join the Software Technology group led by Gabriele Keller. As our research group contains core members of the popular Accelerate and Stan DSLs for machine learning and scientific computing, newly developed techniques could quickly have a large impact and reach a large audience of end users. Beyond Utrecht University, we anticipate collaborating with international partners including the Center for Computational Mathematics at the Flatiron Institute in New York, the Department of Computer Science at the University of Oxford, the Amsterdam Machine Learning Lab, and the XLA and JAX teams at Google.

Your teaching
Teaching will be a small but valuable part of your role within the Department of Information and Computing Sciences. Depending on your interests and our departmental needs, you will contribute to teaching activities of courses such as Probabilistic Reasoning, Machine Learning, Functional Programming, Concurrency, Concepts of Programming Language Design, Languages and Compilers, Logic, or other courses in our BSc and MSc programmes. Activities may include conducting tutorials, student supervision and public outreach. This experience will help you develop teaching skills and explore whether you see a future in academia.

We are looking for a driven new colleague who meets several or all of the following criteria:

• You have a Master’s degree with research experience in Computer Science, Mathematics, Statistics, or Physics, or a related discipline;
• You’re excited about research and you are motivated to explore the areas of differential and probabilistic programming and mathematical aspects of computer science;
• You’re enthusiastic about (and ideally experienced in):
  
  • inference algorithm development and evaluation for statistical computing and machine learning;
  • applications of statistical computing and machine learning;
  • probabilistic and differentiable programming.
• You have strong English communication skills, both in speaking and writing;
• You enjoy working independently, but also thrive in a collaborative, diverse team environment.

Most of all, we value curiosity, initiative, and a passion for science. We welcome candidates who are eager to shape their own research path within the scope of this ERC project.

• a position for 18 months, with an extension to a total of four years upon successful assessment in the first 18 months;
• a working week of 38 hours and a gross monthly salary between €3,059 and €3,881 (salary scale P under the Collective Labour Agreement for Dutch Universities (CAO NU));
• 8% holiday pay and 8.3% year-end bonus;
• a pension scheme, partially paid parental leave and flexible terms of employment based on the CAO NU.

In addition to the terms of employment laid down in the CAO NU, Utrecht University has a number of schemes and facilities of its own for employees. This includes schemes facilitating professional development, leave schemes and schemes for sports and cultural activities, as well as discounts on software and other IT products. We also offer access to additional employee benefits through our Terms of Employment Options Model. In this way, we encourage our employees to continue to invest in their growth. For more information, please visit Working at Utrecht University.

A better future for everyone. This ambition motivates our scientists in executing their leading research and inspiring teaching. At Utrecht University, the various disciplines collaborate intensively towards major strategic themes. Our focus is on Dynamics of Youth, Institutions for Open Societies, Life Sciences and Pathways to Sustainability. Sharing science, shaping tomorrow.

Working at the Faculty of Science means bringing together inspiring people across disciplines and with a variety of perspectives and backgrounds. The Faculty has six departments: Biology, Pharmaceutical Sciences, Information & Computing Sciences, Physics, Chemistry and Mathematics. Together, we work on excellent research and inspiring education. We do so, driven by curiosity and supported by outstanding infrastructure. Visit us on LinkedIn and discover how you can become part of our community.

Within the Department of Information and Computing Sciences, the Software Technology group specialises in work broadly relating to programming languages, functional programming, software correctness, and DSLs for high performance computing. Within the Software Technology group, the FoRECAST team specialises in probabilistic and differential programming languages, for use in scientific computing and machine learning. We are interested in questions ranging from semantic foundations and correctness, via the development of novel probabilistic and differential algorithms, to the development of high-performance implementations in which the rubber meets the road. More generally, we are enthusiastic about a wide range of research topics at the intersection of mathematics and computer science and truly value scientific curiosity. We like to work as a diverse team where every member has their own expertise that complements that of the other team members, allowing us to approach ambitious questions and build a bridge between theoretical foundations and practical applications. Our style of work is a mixture of focused individual work and interdisciplinary collaboration as a team.