Postdoctoral Researcher in Causal Machine Learning

**Faculty of Sciences**:

- **Department: WE02 - Wiskunde, Informatica en Statistiek**:

- **Occupancy rate:100%**:

- **Number of positions: 1**:

- **Type of employment: Contract of unlimited duration with clause**:

- **Term of assignment: 3 years**:

- **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.

**YOUR TASKS**
- At least 70% of your assignment will be spent on academic research.
- Contributing to the development of a general framework for assumption-lean causal and statistical modeling, as part of a team of researchers working on an Advanced ERC Grant (ACME) on this theme.
- Studying, implementing, and advancing techniques in debiased machine learning and orthogonal statistical learning, improving both their statistical efficiency and robustness.
- Translating large-sample statistical results, developed in collaboration with theoretical statisticians, into implementable learning tools.
- Co-mentoring PhD students in the team.
- Producing high-quality scientific publications for top journals and conferences.
- Contributing to the educational mission of our group through limited teaching support and supervision of bachelor/master theses related to the project.

**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, Computer Science, Physics, Engineering, or a related field.
- You have a strong background in machine learning; familiarity with causal inference or debiased machine learning is an asset.
- You are motivated to work at the intersection of machine learning and statistics, translating theoretical insights from mathematical statistics, developed by other team members, into novel learning algorithms. Prior experience at this interface is a strong plus.
- You have proven research excellence, evidenced by high-quality publications.
- You have strong analytical skills, creativity, and the ability to work independently.
- You are a team player with good communication skills.
- You are fluent in English (C1 CEFR level), both written and spoken.

**WHAT WE CAN OFFER YOU**
- We offer you a contract of indefinite duration with a maximum term of 3 years.
- Your contract will start on 1/07/2025 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 staff benefits.
- if the researcher has resided abroad for at least 24 months during the 3 years preceding the start date of the postdoctoral fellowship and has not worked or studied in Belgium during that period.
- if the researcher obtained their doctorate at a non-Belgian university.

**INTERESTED?**
- In the field **‘CV’**: your CV and a transcript of your academic record (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 translation in one of the mentioned languages.
- In the field **“other documents”**: contact details of at least two referees.

Note that the maximum file size for each field is 10 MB.

**MORE INFORMATION