PostDoc in Causal Machine Learning and Reinforcement Learning (3 years)

Vrije Universiteit Amsterdam; Amsterdam; On-site; EUR 41,000 - 64,000; Full time

Benefits offered by this job

Annual leave 41 days

Holiday allowance 8%

End-of-year bonus 8.3%

Theatre discounts

Sports facilities

Commuting allowance

Job summary

Vrije Universiteit Amsterdam invites applications for a PostDoc to advance research at the intersection of machine learning and statistics, with emphasis on causal inference and reinforcement learning in health-related data.

The role sits in the Quantitative Data Analytics group and collaborates with Amsterdam UMC, Erasmus MC and Groningen, offering strong research freedom and the chance to supervise students in a multi-year program, including teaching responsibilities.

Qualifications

• PhD in ML/Statistics or related field.
• Experience in ML and health data applications, demonstrated by publications.
• Strong programming skills in Python with PyTorch or TensorFlow.
• Ability to work independently and in teams.

Responsibilities

• Perform research in ML and statistics and publish in top AI/ML conferences.
• Collaborate with QDA group and partner institutes (Amsterdam UMC, Erasmus MC, Groningen).
• Contribute to Stress in Action and MINMED projects and interact with partners.
• Teach activities and supervise Bachelor/Master students (about 20% of time).

Skills

PhD in ML/Statistics

Experience in ML research

Causal inference expertise

Reinforcement learning

Programming (Python)

Education

PhD in ML/Statistics

Tools

PyTorch

TensorFlow

Job description

Your function

We are looking for a PostDoc who will do research on the intersection ofmachine learning (ML) and statistics. More specifically, the focus is on the development of algorithmic improvements in causal inference and reinforcement learning through the cross fertilization of machine learning and statistical approaches and applying these innovations in a health setting.

The position is embedded in two projects which act as application domains. First of all, the ten-year gravitation grant Stress in Action, funded through NWO (Dutch National Science Foundation). The goal of the project is to move stress research from the lab into daily life, and hence, the use cases of the methodological innovations will focus on applications to stress-related data, such as wearables, ecological momentary assessments, and other types of questionnaires. Secondly, the ZonMW funded MINMED project which aims to unlock causal effects of interventions in elderly care from observational data.

A variety of academic partners are involved in the two projects, including Vrije Universiteit Amsterdam, Amsterdam UMC, Erasmus MC, University of Twente, University of Groningen, UMC Groningen, and Utrecht University.

The position is embedded in the Quantitative Data Analytics (QDA) group of the VU in close collaboration with the Amsterdam UMC, Erasmus MC and the University of Groningen. The QDA group focuses on both fundamental and application-driven research in ML.

We are looking for candidates with experience in the area of machine learning or statistics, with a special preference for those with expertise in causal inference and/or reinforcement learning, ideally complemented with a solid background in statistics. We are interested in attracting a PostDoc who is able to perform ground-breaking research on fundamental aspects of machine learning and statistics and wants to apply these innovations in the context of the Stress in Action and MINMED projects.

Your duties

The PostDoc position is focused on performing research and contains the following duties:

• performing research in the field of machine learning andpublishing in top AI and ML conferences
• participating in the QDA group of VU (lead by Mark Hoogendoorn),the Biostatistics group of Erasmus MC (led by Dimitris Rizopoulos), and Laura Bringmann's intensive longitudinal data lab at the University of Groningen.
• contributing to the Stress in Action and MINMED projects and interacting with the different partners and stakeholders in the project
• contributing to some teaching activities and possibly supervising Bachelor and Master students (20% of the time)

Your profile

We will base our selection on the following components:

• a PhD degree in an area relevant to machine learning and/or statistics
• prior experience in machine learning, ideally also on applications in the health domain, demonstrated by relevant publications
• a strong record of computer programming, with experience in pytorch and/or tensorflow
• demonstrated ability to work both independently and as a team member

As a university, we strive for equal opportunities for all, recognising that diversity takes many forms. We believe that diversity in all its complexity is invaluable for the quality of our teaching, research and service. We are always looking for talent with diverse backgrounds and experiences. This also means that we are committed to creating an inclusive community so that we can use diversity as an asset.

We realise that each individual brings a unique set of skills, expertise and mindset. Therefore we are happy to invite anyone who recognises themselves in the profile to apply, even if you do not meet all the requirements.

What do we offer?

A challenging position in a socially involved organization. The salary will be inaccordance with university regulations for academic personnel and amounts € 3.706,00 per month during the first year and increases to € 5760,00 per month during the fourth year, based on a full-time employment. The job profile: (scale 10) is based on the university job ranking system and is vacant for 1 FTE. The appointment will initially be for a duration of 3 years at VU Amsterdam, including a 2 months probation.

Additionally, Vrije Universiteit Amsterdam offers excellent fringe benefits and various schemes and regulations to promote a good work/life balance, such as:

• a maximum of 41 days of annual leave based on full-time employment,
• 8% holiday allowance and 8.3% end-of-year bonus
• discount on (and occasionally exclusive access to) theater performances and courses at the Griffioen Cultural Center,
• a wide range of sports facilities which staff may use at a modest charge,
• contribution to commuting expenses
  

About us

Computer Science Department
The Department has approximately 220 staff members, including 100 PhD students. University research and teaching staff is a critical and essential basis for the functioning of the department, providing foundational education that helps determine the future of our students. Currently, we offer programs in Computer Science, Artificial Intelligence and Information Sciences (BSc and MSc), Bioinformatics and Systems Biology (MSc), with a total of around 1000 new students each year.

The department explicitly encourages inter- and cross disciplinary research, and expects the successful candidate to be able to collaborate with colleagues in other fields of Computer Science (e.g. Artificial Intelligence and Quantitative Data Analytics, Software and Sustainability, or System Security), as well as with colleagues from other institutes such as CWI. A large share of interdisciplinary research with the department is embedded in the Network Institute of Vrije Universiteit, covering disciplines such as Social sciences, Humanities, and Economics. The Department also actively participates in Amsterdam Data Science, a collaboration between more than 600 data science researchers from different institutions in Amsterdam and AMSec, the Amsterdam security collaborative center with researchers from different institutions in Amsterdam.
Faculty of Science
Working at the Faculty of Science means collaborating with students, lecturers and researchers who are focused on their field, yet have a broad view of the world. We are proud of a positive and inclusive workplace culture within the faculty, where we work together with great energy and a pragmatic attitude to tackle social challenges. At the Faculty of Science, scientists and students work on fundamental and complex societal issues for a sustainable, healthy and just future.

From forest fires to big data, from obesity to malnutrition, from helium to the universe and from genetics to medicine: our education and research cover the full breadth of science, from molecules to mankind. Our academic education and research are highly experimental, technical and interdisciplinary in nature. That is why we collaborate extensively with leading scientific institutes and industry. The faculty has more than 8,000 students studying in one of the 39 programms and employs more than 1,400 staff across 10 scientific departments, making us one of the largest science faculties in the Netherlands.

Vrije Universiteit Amsterdam
Vrije Universiteit Amsterdam stands for values-driven education and research. We are open-minded experts with the ability to think freely - a broader mind. Maintaining an entrepreneurial perspective and concentrating on diversity, significance and humanity, we work on sustainable solutions with social impact. By joining forces, across the boundaries of disciplines, we work towards a better world for people and planet. Together we create a safe and respectful working and study climate, and an inspiring environment for education and research. Learn more about our codes of conduct

We are located on one physical campus, in the heart of Amsterdam's Zuidas business district, with excellent location and accessibility. Over 6,150 staff work at the VU and over 31,000 students attend academic education.

Diversity
Diversity is the driving force of VU Amsterdam. VU wants to be accessible and receptive to diversity in disciplines, cultures, ideas, nationalities, beliefs, preferences and worldviews. We believe that trust, respect, interest, and differences lead to new insights and innovation, to sharpness and clarity, to excellence and a broader understanding.

We stand for an inclusive community and believe that diversity and internationalisation contribute to the quality of education, research and our services.

Therefore, we are always searching for people whose backgrounds and experience contribute to the diversity of the VU community.
About the department
The VU Department of Computer Science has approximately 250 members, including 70 tenured staff members.