Associate Professor in Fundamental Machine Learning

Unlock the Power of Machine Learning: Delve into the Fundamentals of Machine Learning for a Deeper Understanding.

Challenge: Understanding the fundamentals of machine learning.

Change: Conducting theoretical and experimental research on machine learning to gain new insights.

Impact: Exploit machine learning insight to drive solving key societal problems

Machine learning is a driving force behind many AI developments that are profoundly transforming our society. To optimally use this disruptive technology to solve major societal problems, we need to grasp AI learning at the most elementary level. We do, however, still have a partial understanding of the behaviour of machine learning methods and under what conditions learning is possible. For example, how do you generalize from small data sets, or how do you generalize to new settings and under which assumptions. Or, how do you continuously learn, learn to learn (meta-learning), or incorporate existing knowledge within machine learning models (like physics-informed machine learning, or graph-based models). You get inspired by these fundamental questions and have a drive to understand why learning is possible, and how data can most optimally be used. As an Associate Professor in Fundamental Machine Learning at TU Delft you will help us explore these foundational questions.

This position offers an exciting opportunity to contribute to innovative research and shape the future of machine learning. You will join our Computer Science department as part of the Pattern Recognition & Bioinformatics group, which has a long history of research in pattern recognition and machine learning. You will be part of a dynamic, collaborative and socially active academic team of 15 Principal Investigators and 50 PhD students dedicated to machine learning. With an inclusive mix of nationalities, perspectives, and backgrounds, we are united in the goal to understand and leverage AI for societal good in domains like healthcare, climate change, energy and food production, among others.

In this role, you will lead cutting-edge research initiatives, actively engage in interdisciplinary collaborations, publish your findings in top-tier academic journals and secure external funding to support your research endeavours. Furthermore, you will contribute to and shape machine learning education and mentor aspiring students, facilitating their growth and development in the field of machine learning.

Relevant links:

PR lab

INSY department

AI&digitalisation TUD

TUD Ellis unit

With your people-oriented attitude, having constructive discussions and networking with colleagues, students and external partners comes easy to you. Because you’ll have to operate in an international environment, you speak and write English fluently, and are willing to learn Dutch if you don’t speak it already. You are excited about the future of machine learning and a visionary when it comes to selecting innovative research directions.

You also have:

• A PhD in Computer Science, Statistics, or a related field.
• Proven research performance in machine learning or related areas demonstrated through a strong publication record.
• The leadership capabilities to guide research teams.
• The ability to secure research funding by convincing key decision-makers of your research proposals.
• A passion for contributing to world-class education, with experience teaching academically and supervising bachelor’s, master’s and postgraduate students.

Salary and benefits are in accordance with the Collective Labour Agreement for Dutch Universities. The TU Delft offers a customisable compensation package, discounts on health insurance, and a monthly work costs contribution. Flexible work schedules can be arranged.

Inspiring, excellent education is our central aim. We expect you to obtain a University Teaching Qualification (UTQ) within three years if you have less than five years of teaching experience. This is provided by the TU Delft UTQ programme.

TU Delft sets high standards for the English competency of the teaching staff. The TU Delft offers training to improve English competency. If you do not speak Dutch, we offer courses to learn the Dutch language.

For international applicants, TU Delft has the Coming to Delft Service . This service addresses the needs of new international employees and those of their partners and families. The Coming to Delft Service offers personalised assistance during the preparation of the relocation, finding housing and schools for children (if applicable). In addition, a Dual Career Programme  for partners is offered. The Coming to Delft Service will do their best to help you settle in the Netherlands.

 Delft University of Technology is built on strong foundations. As creators of the world-famous Dutch waterworks and pioneers in biotech, TU Delft is a top international university combining science, engineering and design. It delivers world class results in education, research and innovation to address challenges in the areas of energy, climate, mobility, health and digital society. For generations, our engineers have proven to be entrepreneurial problem-solvers, both in business and in a social context.

At TU Delft we embrace diversity as one of our core values  and we actively engage  to be a university where you feel at home and can flourish. We value different perspectives and qualities. We believe this makes our work more innovative, the TU Delft community more vibrant and the world more just. Together, we imagine, invent and create solutions using technology to have a positive impact on a global scale. That is why we invite you to apply. Your application will receive fair consideration.

Challenge. Change. Impact!

The Faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS) brings together three scientific disciplines. Combined, they reinforce each other and are the driving force behind the technology we all use in our daily lives. Technology such as the electricity grid, which our faculty is helping to make completely sustainable and future-proof. At the same time, we are developing the chips and sensors of the future, whilst also setting the foundations for the software technologies to run on this new generation of equipment – which of course includes AI. Meanwhile we are pushing the limits of applied mathematics, for example mapping out disease processes using single cell data, and using mathematics to simulate gigantic ash plumes after a volcanic eruption. In other words: there is plenty of room at the faculty for ground-breaking research. We educate innovative engineers and have excellent labs and facilities that underline our strong international position. In total, more than 1000 employees and 4,000 students work and study in this innovative environment.

Click here  to go to the website of the Faculty of Electrical Engineering, Mathematics and Computer Science.

If you would like more information about this role, please contact Marcel Reinders, Professor, at [email protected] 

Are you our new Associate Professor in Fundamental Machine Learning? Upload your motivation letter, CV, along with your research, education and leadership visions, before April 15 2024. 

• A pre-employment screening can be part of the selection procedure.
• You can apply online. We will not process applications sent by email and/or post.
• Please do not contact us for unsolicited services.