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Postdoctoral Fellow in Causal Machine Learning
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**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:PhD**
**ABOUT GHENT UNIVERSITY**
Ghent 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.
- Collaborating with fellow researchers to develop foundations for a generic paradigm for assumption-lean causal/statistical modeling.
- Writing high quality publications, targeting top journals and international conferences.
**WHAT WE ARE LOOKING FOR**
- 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.
**WHAT WE CAN OFFER YOU**
- 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. Click here for more information about our salary scales.
- 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.. Click here for a complete overview of all the staffbenefits (in Dutch).
**INTERESTED?**
- In the field **‘CV’**: your CV and an overview of your study results (merged into one pdf file)
- 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 transl
