PhD Position: Sustainability of Scalable AI

This PhD project focuses on developing methods to assess the sustainability of nearly 100 nationwide AI systems within the National Lab on Education and AI (NOLAI). You will create methods to predict energy consumption, create energy labels for algorithm scalability, and guide implementers in choosing more efficient algorithms. Ready to make AI more sustainable? Apply now!

The goal of your PhD project is to develop methods to steer developments of large AI systems in such a way that they are environmentally sustainable. To this end, different designs of AI systems should be assessed during the design phase. Data flow diagrams are already used in NOLAI, and capture all the processing, storing and transmission of data: elements in the environmental impact of IT systems. You can extend these data flow diagrams with the expected environmental impact so different design variants can be considered by the team working on these systems.

You will measure and fill the unknowns uncovered in such a data flow diagram. The scalability of the core algorithms of a new nationwide AI system can be predicted using generated data sets of different sizes and measuring the environmental impact. This impact can be measured and calculated using our Software Energy Lab, which has multiple test machines with GPUs and, in the future, AI accelerators.

Development teams currently lack guidance on how to create sustainable systems. You will develop a method to help development teams choose the right algorithm and right hardware. This can be done by measuring (during the above-mentioned experiments) how the algorithms are constrained. They can be constrained by either compute power or memory bandwidth. This information can be used to calculate the theoretical maximum energy efficiency of an algorithm that is run on an architecture/accelerator. To make testing multiple architectures easier, you will leverage our existing approach to generate code from a single source code for multiple architectures and accelerators, called SaC.

You will create a way to disseminate the scalability and environmental impact within NOLAI. To this end, sustainable scalability labels of core algorithms should be made available within NOLAI. These labels can be used to design new systems. What should be included in these labels is part of this PhD research project. You will collaborate with scientific staff and PhD candidates from different disciplines and with a small team of software developers working on AI prototypes and infrastructure.

There is no teaching load in this position.

• We will give you a temporary employment contract (1.0 FTE) of 1.5 years, after which your performance will be evaluated. If the evaluation is positive, your contract will be extended by 2.5 years (4-year contract).
• You will receive a starting salary of €2,901 gross per month based on a 38-hour working week, which will increase to €3,707 in the fourth year (salary scale P).
• You will receive an 8% holiday allowance and an 8,3% end-of-year bonus.
• You will receive extra days off. With full-time employment, you can choose between 30 or 41 days of annual leave instead of the statutory 20.

Work and science require good employment practices. This is reflected in Radboud University's primary and secondary employment conditions. You can make arrangements for the best possible work-life balance with flexible working hours, various leave arrangements and working from home. You are also able to compose part of your employment conditions yourself, for example, exchange income for extra leave days and receive a reimbursement for your sports subscription. And of course, we offer a good pension plan. You are given plenty of room and responsibility to develop your talents and realise your ambitions. Therefore, we provide various training and development schemes.

The position is at Radboud University's Institute for Computing and Information Sciences (iCIS) as part of the NOLAI project. NOLAI, the National Education Lab AI, funded by the Dutch National Growth Fund, represents the largest public investment worldwide in the field of AI and education. It is a 10-year project involving multiple universities, schools and non-academic partners. The goal is to have a long-lasting positive impact by combining scientific, educational and commercial perspectives.

iCIS is an internationally recognised institute that is consistently ranked among the top Computer Science departments in the Netherlands. It comprises an enthusiastic and devoted team of excellent researchers that closely collaborate in a flat organisational structure. The institute focuses its research on three themes: data science, digital security and software science. Each of these themes spans the full breadth from fundamental research to application-oriented research. Our long-term drive is to contribute to both science and society. iCIS staff members are also responsible for the Bachelor’s and Master’s programmes in Computer Science, the Master’s programme in Information Science, and for about 30% of the Bachelor’s and Master’s programmes in AI at Radboud University. iCIS staff have a high level of freedom to determine the way they structure the work they do. Over the past few years, the institute has made a strong effort to increase the diversity of its staff. More than half of our academic staff have an international background.

You can apply only via the button below. Address your letter of application to Bernard van Gastel. In the application form, you will find which documents you need to include with your application.

The first interviews will take place on Tuesday 6 May. You will preferably start your employment as soon as possible.

We can imagine you're curious about our application procedure. It describes what you can expect during the application procedure and how we handle your personal data and internal and external candidates.