Assistant Professor in Machine Learning at Maastricht University

January 16, 2024

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Job Description


Are you passionate about designing versatile machine learning algorithms and statistical models that can learn from different and diverse types of data? 

Job Description

Do you want to delve even deeper into how machine learning algorithms work, including the consequences of algorithmic design on fairness, bias, and transparency? Are you eager to contribute to new developments in machine learning to advance our understanding of recommender systems and reinforcement learning, and how to use them to solve complex problems that evolve over longer periods of time? Do you value seeing your research applied to real-world challenges from different domains (like healthcare or manufacturing) to address urgent societal needs? 

If you see yourself making an impact in any of these areas – or you have other interesting machine learning topics to bring to the table – you should consider joining our Department of Advanced Computing Sciences (DACS) as an Assistant Professor in Machine Learning. DACS is an international community of ~100 researchers at various stages of their career, embedded in the Faculty of Science and Engineering (FSE). Our department has more than 30 years’ experience with research and teaching in the fields of Artificial Intelligence, Computer Science and Applied Mathematics. 

What are you going to do

To strengthen our research initiatives on machine learning, we are looking for a scientist with expertise in areas such as: reinforcement learning, recommender systems, automatic discovery of data representations and data set relations. Research on emerging machine-learning topics, for instance: sustainable machine learning, multi-objective recommendation, multi-agent reinforcement learning, and application of machine learning in medicine – are particularly welcome. As an Assistant Professor you will also be active in acquiring research funding and support fellow junior researchers. 

As our new colleague, you will contribute to DACS research. Our research activities span the entire spectrum from curiosity-driven research to responsible societal applications, often taking on an interdisciplinary character. Contributions to areas such as multi-agent systems, (medical) signal and image processing, FAIR principles, game theory, intelligent search techniques and affective computing are internationally recognized. What makes our research so interesting is that DACS maintains an industry network with over 80 private collaborators ranging from local SMEs to large multinationals. The department designs and develops data-driven solutions for a wide variety of business applications in sectors including transport and logistics, healthcare, and production and manufacturing. This why you can contribute to science and our society of tomorrow! 

In addition to your research, you will contribute to our top-rated education. Our department offers one bachelor’s program and two master programs in the fields of AI and Data Science, all of which are nationally ranked among the top of their kind. In September 2023, we have also launched a new bachelor in Computer Science. You will strongly contribute to the focus and strengthening of our programs. 

Job Requirements

Who are you? 

We seek a colleague who is passionate about research and who enjoys teaching. You feel at home in a strongly international and diverse community like ours. Furthermore, we are looking to welcome someone who fosters collaboration at all levels. 

Our ideal candidate has:

  • A PhD degree in Machine Learning or a strongly related field;
  • Ideally, preferably 2 years or more working experience in an academic environment post-PhD;
  • A proven track record in research and teaching, commensurate with the rank of assistant professor;
  • Experience with funding acquisition;
  • Effective communication (in English) and organizational skills;
  • Experience of remote and online teaching is a bonus; 

What we offer

As Assistant Professor in Machine learning at Faculty of Science & Engineering, you will be employed by the most international university in the Netherlands, located in the beautiful city of Maastricht. In addition, we offer you: 

  • Good employment conditions. The position is graded in scale 11 according to UFO profile Assistant Professor, with corresponding salary based on experience ranging from €4332.00 and €5929.00 gross per month (based on a full-time employment of 38 hours per week). In addition to the monthly salary, an 8.0% holiday allowance and an 8.3% year-end bonus apply.
  • An employment contract for a period of 18 months with a scope of 1,0 FTE. Upon proven suitability, the employment contract will be converted to an indefinite contract.
  • At Maastricht University, the well-being of our employees is of utmost importance, we offer flexible working hours and the possibility to work partly from home if the nature of your position allows it. You will receive a monthly commuting and internet allowance for this. If you work full-time, you will be entitled to 29 vacation days and 4 additional public holidays per year, namely carnival Monday, carnival Tuesday, Good Friday, and Liberation Day. If you choose to accumulate compensation hours, an additional 12 days will be added. Furthermore, you can personalize your employment conditions through a collective labor agreement (CAO) choice model.
  • As Maastricht University, we offer various other excellent secondary employment conditions. These include a good pension scheme with the ABP and the opportunity for UM employees to participate in company fitness and make use of the extensive sports facilities that we also offer to our students.
  • Last but certainly not least, we provide the space and facilities for your personal and professional development. We facilitate this by offering a wide range of training programs and supporting various well-established initiatives such as ‘acknowledge and appreciate’.
  • The terms of employment at Maastricht University are largely set out in the collective labor agreement of Dutch Universities. In addition, local provisions specific to UM apply. For more information, click here

Maastricht University

Why work at Maastricht University? 

At Maastricht University (UM), everything revolves around the future. The future of our students, as we work to equip them with a solid, broad-based foundation for the rest of their lives. And the future of society, as we seek solutions through our research to issues from all around the world. Our six faculties combined provide a comprehensive package of study programmes and research. 

In our teaching, we use the Problem-Based Learning (PBL) method. Students work in small groups, looking for solutions to problems themselves. By discussing issues and working together to draw conclusions, formulate answers and present them to their peers, students develop essential skills for their future careers. 

With over 22,300 students and more than 5,000 employees from all over the world, UM is home to a vibrant and inspiring international community. 

Are you drawn to an international setting focused on education, science and scholarship? Are you keen to contribute however your skills and qualities allow? Our door is open to you! As a young European university, we value your talent and look forward to creating the future together. 

Click here for more information about UM. 

Faculty of Science and Engineering  

At the Faculty of Science and Engineering (FSE), we focus on themes such as circularity and sustainability, future farming, digitisation and (scientific) instrument development.  FSE’s leading projects, like the Einstein Telescope Pathfinder, are sure to grab anyone’s attention.  The faculty is a vibrant hub of education and research in Science, Technology, Engineering, and Mathematics (STEM) and Liberal Arts and Sciences (LAS).  At FSE, over 450 staff members and 3700 students gather to explore e exciting interdisciplinary research and educational programmes. Feel welcome, be part of our team and put your brilliant mind to work! 

FSE at the Brightlands Campuses

Maastricht, Sittard-Geleen, Heerlen, and Venlo, the home of four creative Brightlands campuses, are bustling with 30,000 entrepreneurs, researchers, and students working diligently to solve global challenges. The Faculty of Science and Engineering is active on all four Brightlands campuses, and this is where our impact reaches its peak. To give you an idea of what is happening at each campus: Sittard-Geleen is home to the largest chemical site in the Euregion, while Venlo is a large hub for agri-food innovation. Maastricht is the site of the Health Campus, and Heerlen is the place to be for Smart Services. 

Department of Advanced Computing Sciences

The Department of Advanced Computing Sciences is Maastricht University’s largest and olders department broadly covering the fields of artificial intelligence, data science, computing science, mathematics and robotics. 

Over 100 researchers work and study in the Department of Advanced Computing Sciences, whose roots trace back to 1987. The department’s staff teaches more than 1,200 bachelor’s and master’s students in 4 specialized study programmes in Data Science, Artificial Intelligence and Computing Science. 

Curious?

Are you interested in this exciting position but still have questions? Feel free to contact Mark Winands via m.winands@maastrichtuniversity.nl for more information. 

Applying?

Or are you already convinced and ready to become our new Assistant Professor in Machine learning? Apply now, no later than 3 March, for this position. 

The vacancy is open for internal and external candidates. In case of equal qualifications, internal candidates will be prioritized. 

Maastricht University is committed to promoting and nurturing a diverse and inclusive community. We believe that diversity in our staff and student population contributes to the quality of research and education at UM, and strive to enable this through inclusive policies and innovative projects led by teams of staff and students. We encourage you to apply for this position.





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