Machine learning techniques have seen a tremendous increase of adoption over the last decade and this growth has been fueled by both advances on the algorithmic level and the ability to leverage hardware acceleration for making the algorithms run at scale. However, as ML models increasingly supplement or replace traditional business logic in decision making processes, it is critical to develop an understanding of how machine learning can be deployed at scale. Important considerations are the deployment, testing, and long-term maintenance of models. The goal is to investigate the systems aspects and building tools for automating this process.

Candidates are expected to have experience in writing efficient code and conducting scientific evaluations through experimentations. The position is for our four-year PhD program and remuneration follows the COA (collective labor agreement) for Dutch universities.

The selected candidate will work in close collaboration with the ICAI Center AI for Fintech Research, a joint initiative of TU Delft and ING bank. Our department is committed to the principle of equal employment opportunity for all employees and we strive to building a team that represents a variety of backgrounds, perspectives, and skills. We explicitly encourage suitable candidates of all genders and with disabilities to apply.

Fixed-term contract: 4 years.

TU Delft offers a customisable compensation package, a discount for health insurance and sport memberships, and a monthly work costs contribution. Flexible work schedules can be arranged. An International Children’s Centre offers childcare and an international primary school. Dual Career Services offers support to accompanying partners. Salary and benefits are in accordance with the Collective Labour Agreement for Dutch Universities.
As a PhD candidate you will be enrolled in the TU Delft Graduate School. TU Delft Graduate School provides an inspiring research environment; an excellent team of supervisors, academic staff and a mentor; and a Doctoral Education Programme aimed at developing your transferable, discipline-related and research skills. Please visit www.tudelft.nl/phd for more information.

Technische Universiteit Delft

Delft University of Technology (TU Delft) is a multifaceted institution offering education and carrying out research in the technical sciences at an internationally recognised level. Education, research and design are strongly oriented towards applicability. TU Delft develops technologies for future generations, focusing on sustainability, safety and economic vitality. At TU Delft you will work in an environment where technical sciences and society converge. TU Delft comprises eight faculties, unique laboratories, research institutes and schools.

Faculty Electrical Engineering, Mathematics and Computer Science

The Faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS) is known worldwide for its high academic quality and the social relevance of its research programmes. The faculty’s excellent facilities accentuate its international position in teaching and research. Within this interdisciplinary and international setting the faculty employs more than 1100 employees, including about 400 graduate students and about 2100 students. Together they work on a broad range of technical innovations in the fields of sustainable energy, telecommunications, microelectronics, embedded systems, computer and software engineering, interactive multimedia and applied mathematics.

The Department of Software Technology (ST) is one of the leading Dutch departments in research and academic education in computer science, employing over 150 people. The department ST is responsible for a large part of the curriculum of the bachelor’s and master’s programmes in Computer Science as well as the master’s programme in Embedded Systems. The inspiration for its research topics is largely derived from technical ICT problems in industry and society related to large-scale distributed processing, embedded systems, programming productivity, and web-based information analysis.