Postdoctoral Fellow in Causal Machine Learning

Job title:

Postdoctoral Fellow in Causal Machine Learning


Job description

Offer Description→ Apply before 01/09/2024 (DD/MM/YYYY) 23:59 (Brussels Time)
→ Faculty of Sciences
→ Department: WE02 – Toegepaste Wiskunde, Informatica en Statistiek
→ Occupancy rate: 100%
→ Number of positions: 1
→ Type of employment: Contract of unlimited duration with clause
→ Term of assignment: 4 jaar
→ Wage scale: PD1 to PD4 (doctoral degree)
→ Required diploma: PhDABOUT GHENT UNIVERSITYGhent University is a world of its own. Employing more than 15,000 people, it is actively involved in education and research, management and administration, as well as technical and social service provision on a daily basis. It is one of the largest, most exciting employers in the area and offers great career opportunities. With its 11 faculties and more than 80 departments offering state-of-the-art study programmes grounded in research in a wide range of academic fields, Ghent University is a logical choice for its staff and students.The Causal Inference research lab at Ghent University is seeking a highly motivated and talented postdoctoral fellow to join its team. Ghent University has a long tradition of research in causal inference since the mid 90’s, and now has a vibrant causal inference community comprising over 20 statisticians dedicated to advancing this field.This postdoctoral position is one of multiple positions being opened in connection to Advanced ERC Grant ACME ‘Assumption-lean (Causal) Modeling and Estimation’. In an era where the focus on causal inference is increasingly turning away from modeling towards quantifying population-level intervention effects, there is a risk of oversimplifying causal queries and of neglecting the rich history and efficacy of statistical modeling techniques. This ERC project aims to bridge this gap by leveraging the flexibility and power of statistical models to accurately represent intervention effects or facets of the causal data-generating mechanism, integrating it with recent insights from debiased machine learning and causal inference. Besides laying foundations for a novel paradigm for causal/statistical modeling, this project seeks to enhance the robustness and efficiency of debiased machine learning methods. This postdoc project will primarily focus on this latter component and on the development of techniques for orthogonal statistical learning, in interaction with fellow researchers on this project.YOUR TASKS

  • At least 70% of your assignment will be spent on academic research.
  • Studying, implementing, developing and improving state-of-the-art techniques for debiased machine learning and orthogonal statistical learning, to enhance their robustness and statistical efficiency.
  • Using techniques from asymptotic statistics and empirical process theory, along with Monte Carlo simulation studies, to examine the large and finite-sample properties of the developed estimators.
  • Applying or supervising application of the developed techniques for debiased machine learning or orthogonal statistical learning in substantive case studies with real world medical data.
  • Collaborating with fellow researchers to develop foundations for a generic paradigm for assumption-lean causal/statistical modeling.
  • Mentoring PhD students who collaborate on the above subjects.
  • Writing high quality publications, targeting top journals and international conferences.
  • In addition to your primary research responsibilities, you will actively contribute to the educational mission of our institution by providing (limited) support for courses in (mathematical) statistics. In addition, you take on a mentoring role by supervising bachelor or master theses related to the subject of this project.


  • You hold a thesis-based doctorate (obtained max. 6 years ago. This term of 6 years is determined by the date written on the above-mentioned required diploma) in Statistics, Mathematics, Physics, Computer Science, Engineering (each with a strong strong component on mathematical statistics), or equivalent.
  • You have a strong background in mathematical statistics; familiarity with empirical process theory, causal inference or debiased machine learning is a plus.

You have a proven track record of successful research and high ranked publications in journals that publish statistical methodology. * You have the ability to work autonomously, are creative and have strong analytical skills.

  • You are a team player, ready to be the key link between multiple researchers involved in this project, and have strong communication skills.
  • Your English is fluent (C1 CEFR level) both speaking and writing.


  • We offer you a contract of indefinite duration with a maximum term of 4 years.
  • Your contract will start on 1/10/2024 at the earliest.
  • Your remuneration will be determined by salary scale PD1.

. * All Ghent University staff members enjoy a number of benefits, such as a wide range of training and education opportunities, 36 days of holiday leave (on an annual basis for a full-time job) supplemented by annual fixed bridge days, a bicycle allowance and eco vouchers..
(in Dutch).INTERESTED?Apply online through the e-recruitment systembefore the application deadline (see above). We do not accept late applications or applications that are not submitted through the online system.Your application must include the following documents:

  • In the field ‘CV’: your CV and an overview of your study results (merged into one pdf file)
  • In the field ‘Cover letter’: your application letter in pdf format. Please limit this letter to at most 2 pages (highlighting why you believe you are a suitable candidate for the position, why you want this position, what relevant skills you have developed, and including a research statement).
  • In the field ‘Diploma’: a transcript of the required degree (if already in your possession). If you have a foreign diploma in a language other than our national languages (Dutch, French or German) or English, please add a translation in one of the mentioned languages.
  • In the field “other documents”: at least two reference contacts.

Note that the maximum file size for each field is 10 MB.As Ghent University maintains an equal opportunities and diversity policy, everyone is encouraged to apply for this position.MORE INFORMATIONFor more information about this vacancy, please contact Prof. Stijn Vansteelandt ( , +32(0)9/264 47 76). Important: do NOT send your application by email, but apply online.RequirementsResearch Field Computer science Years of Research Experience 4 – 10Research Field Mathematics Years of Research Experience 4 – 10Research Field Mathematics Years of Research Experience 4 – 10Research Field Mathematics Years of Research Experience 4 – 10Additional InformationWebsite for additional job detailsWork Location(s)Number of offers available 1 Company/Institute Ghent University Country Belgium City Ghent Postal Code 9000 Street Sint-Pietersnieuwstraat 33Where to apply WebsiteContact CityGhent WebsitePostal Code9000STATUS: EXPIRED

Expected salary


Gand, Flandre-Orientale

Job date

Sun, 02 Jun 2024 03:51:00 GMT

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