[Fully Funded PhD Position] Fair and Privacy-Preserving Reinforcement Learning for Healthcare – University of Orléans, France – Deadline Sep 8, 2025

[pratik gajane]

Dear Colleagues,

I am pleased to invite applications for a fully funded PhD position under my supervision at the University of Orléans, France. The position is open to international candidates, and English will be the primary language for all research activities.  Applications will be reviewed on a rolling basis. For full consideration, apply no later than September 8, 2025.  Applications received after this date will be considered if the position remains open.

Topic: Fair and Privacy-Preserving Reinforcement Learning for Healthcare Applications

Research Focus: This PhD project addresses two core challenges: (1) developing fairness-aware reinforcement learning (RL) algorithms for personalized treatment recommendations that ensure equitable outcomes across patient demographics, and (2) designing privacy-preserving RL frameworks that maintain strong privacy guarantees while enabling effective healthcare recommendations. A key methodological focus across both challenges is handling non-stationary environments where patient conditions and treatment protocols evolve over time. The research emphasizes both theoretical rigor and practical validation, seeking mathematical guarantees alongside empirical evaluation using real-world datasets. The balance between mathematical analysis and empirical work can be adjusted based on the student's background and interests.

Collaboration Opportunities: The student will collaborate with leading institutions in France, including CNRS Orléans, CHU Orléans, and other French collaborators, as well as international partners such as the University of Michigan and institutions in India and the Netherlands. This network provides access to clinical datasets, direct collaboration with clinicians, and opportunities for international research visits, subject to research alignment and timing.

Expected Student Characteristics: 
• Education: Master's degree (or equivalent) in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Applied Mathematics, or a closely related field. Candidates with strong quantitative backgrounds in other disciplines (e.g., Statistics, Engineering, Bioinformatics) will also be considered if they demonstrate relevant experience in machine learning. 
• Technical Foundation: Strong background in machine learning and reinforcement learning with solid programming skills. Mathematical proficiency in probability, statistics, and optimization. Prior exposure to fairness-aware ML, privacy-preserving AI, or healthcare applications is beneficial but not a prerequisite. 
• Research Aptitude: Demonstrated ability to conduct independent research. Strong analytical and problem-solving skills. 
• Professional Skills: Excellent communication abilities. Self-motivated with ability to work both independently and as part of research teams. 
• Language Requirements: C1 level proficiency (or equivalent) in English is essential. French language skills are not mandatory.

Application Process:
To apply, please send an email to pratik...@gmail.com with the subject line: [PhD Application 2025a] - Your Full Name. Please combine all required documents into a single PDF file with the same name as your email subject line (maximum file size: 20MB) and include the following:
• Detailed CV highlighting relevant experience (including a list of publications, if applicable).
• Motivation letter (max 2 A4 pages) explaining how your qualifications, skills, and experiences relate to the research topic. Please also describe specific areas within the PhD subject that interest you most and demonstrate your preparedness for these areas.
• Degree certificates and academic transcripts for both BSc and MSc degrees (if the final MSc certificate or transcripts are not yet available, submit provisional transcripts initially; the final versions must be submitted later).
• Contact details for 2-3 referees who can provide recommendation letters.
• English language certificate (TOEFL, IELTS, or equivalent for non-native speakers). If not available, please describe your English language background, such as degrees from English-medium institutions, published papers in English, or equivalent demonstrated proficiency.

Expected Start Date: November 2025 (some flexibility possible based on candidate availability)

Stipend and Benefits:
This PhD position is fully funded by the French National Research Agency (ANR). The PhD candidate will receive a gross monthly stipend of approximately €2,200, with annual increases as per French PhD salary regulations. The precise stipend amount, depending upon standard French PhD salary regulations, will be specified in the formal offer. The position includes typical French PhD benefits and social security coverage, comprehensive career mentorship, and full funding for research-related travel including conference presentations and other activities directly relevant to the research project.

Place of Work:
The Laboratoire d'Informatique Fondamentale d'Orléans (LIFO) at the University of Orléans offers a supportive research environment with experienced faculty and good facilities for PhD students. LIFO members regularly lead and contribute to French and international research projects (full list: https://www.univ-orleans.fr/ lifo/projets ). Orléans is a thriving city with a vibrant student community, reasonable living costs, with the added benefit of easy access to Paris (1 hour by train, 1.5 hours by car), providing an excellent base for both academic work and quality of life.

Contact: Candidates interested in discussing the position and research opportunities are welcome to email pratik...@gmail.com with their CV and a brief summary of their background and research interests to arrange an online meeting.

Best regards,
Dr. Pratik Gajane
Chaire de Professeur Junior ANR (Competitive Research Chair funded by the French National Research Agency - ANR)
LIFO Laboratory
University of Orléans, France