Postdoc Position in Quantized Reinforcement Learning

Syddansk Universitet (University of Southern Denmark - SDU); Odense; On-site; DKK 430,000 - 520,000; Full time

Job summary

University of Southern Denmark's ADIN Lab invites applications for a two-year postdoctoral fellowship in quantized reinforcement learning, to be filled by 1 November 2026. The project targets embodied quantization, discrete world models, and uncertainty-aware RL with non-stationary latent spaces.

Applicants should have a PhD and a strong publication record. Join a vibrant team in Odense under IMADA, collaborating to publish at NeurIPS/ICML/ICLR/AISTATS and contribute to teaching duties.

Qualifications

• PhD in relevant fields at employment time.
• Two first-author papers in flagship ML venues (NeurIPS/ICML/ICLR/AISTATS).
• Strong theoretical grounding in statistical learning and RL; capable of analysis of regret/convergence.

Responsibilities

• Publish in top ML venues and contribute to ADIN Lab output.
• Develop and benchmark quantized RL algorithms and world models.
• Fulfill standard teaching assistant duties as part of the position.

Skills

Python

PyTorch/JAX

Theoretical understanding

Communication in English

Education

PhD in Computer Science

PhD in Mathematics

PhD in Statistics

PhD in Theoretical Physics

Tools

Public repositories

Job description

The SDU Adaptive Intelligence Lab (ADIN Lab) (https://adinlab.github.io/) located under the Data Science and Statistics Section of the Department of Mathematics and Computer Science (IMADA) at the University of Southern Denmark invites applications for a postdoctoral research fellowship position within the field of quantized reinforcement learning to be filled earliest by 1 November 2026 for a period of two years.

About the Project

The project focuses on the theoretical grounding and algorithmic realization of embodied quantization—investigating how continuous sensory inputs are distilled into discrete tokens (such as concepts and objects) to facilitate control in complex environments. Key responsibilities include bridging high-capacity generative representations and discrete world models with non-stationary, risk-sensitive reinforcement learning theory. To achieve this, the candidate will develop uncertainty-aware parsimonious world models (e.g., via evidential learning) and prove finite-sample or regret guarantees under non-stationary latent state spaces, validating these algorithms by building scalable prototypes and benchmarking across high-dimensional simulation suites.

Research Environment

IMADA uniquely brings mathematicians and computer scientists together within a single department to foster theoretically well-backed, high-quality data science research. The department is home to numerous externally funded research projects, and the Data Science and Statistics Group serves as a vibrant synergy platform for experts across fields. The successful candidate will join the ADIN Lab, collaborate on publishing at top-tier venues (NeurIPS, ICML, ICLR, AISTATS), and fulfill standard teaching assistantship duties.

Expected Skills and Qualifications

We are seeking a candidate with a strong desire to make significant contributions to fundamental machine learning research, possessing a combination of mathematical maturity and advanced engineering skills:

• Education: A PhD in Computer Science, Mathematics, Statistics, or Theoretical Physics at the time of employment.
• Publication Track Record: At least two first-author research papers at flagship venues of core machine learning research (e.g., NeurIPS, ICML, ICLR, AISTATS).
• Theoretical Rigor: A deep understanding of statistical learning theory and reinforcement learning foundations, with the ability to conduct performance, convergence, or regret bound analysis (e.g., optimistic posterior sampling) in discrete or latent non-stationary environments.
• Implementation Expertise: Outstanding scientific programming skills (Python, PyTorch/JAX) with a proven track record of developing, debugging, and scaling deep generative models, discrete codebook world models, or complex RL pipelines. Clean public repositories or released source code from past publications is a strong plus.
• Algorithmic Breadth: Familiarity with probabilistic machine learning, evidential learning, discrete variational autoencoders (VQ-VAEs), transformers, or model-based RL is highly desirable.
• Communication: Excellent spoken and written communication skills in English.

Place of work

The Department of Mathematics and Computer Science is located at the main campus of the University of Southern Denmark, Odense, Denmark. The University of Southern Denmark was founded in 1966 and now has more than 27,000 students, almost 20% of whom are from abroad. It has more than 3,800 employees, and 115 different study programmes in the fields of the humanities, social sciences, natural sciences, health sciences, and engineering. Its main campus is located in Odense, the third largest city in Denmark. Odense provides family-friendly living conditions with the perfect combination of a historic city centre with an urban feel and yet a close proximity to beaches and recreational areas. Its location on the beautiful island of Funen is ideal with easy access by train or highway to the bigger cities of Aarhus and Copenhagen. As the birthplace of Hans Christian Andersen, Denmark’s famous fairytale author, the city is home to a vibrant and creative population that hosts numerous festivals and markets throughout the year.

For further questions about the position please contact Prof. Melih Kandemir on [e-mail].

We recommend that as an international applicant, you take the time to visit Work in Denmark where you will find information and facts about moving to, working and living in Denmark, as well as the International Staff Office at SDU.

Application, salary etc.

The successful applicant will be employed in accordance with the agreement between the Ministry of Finance and AC (the Danish Confederation of Professional Associations). Please check links for more information on salary (only available in Danish) and taxation.

Salary is determined in accordance with the applicable collective agreement and based on objective and gender-neutral criteria, including the content of the position, responsibilities, and qualification requirements.

As an applicant, you are entitled to information about the starting salary and salary range for the position. This information will be provided during the recruitment process.

SDU does not collect information on applicants’ previous salary.

The application must include the following:

• A curriculum vitae including information on previous employment with start and end dates
• A full list of publications stating the scientific publications on which the applicant wishes to rely
• Copy of PhD diploma, if Phd diploma has not yet been received, please include statement from your supervisor

Shortlisting may be used in the assessment process.

Incomplete applications and applications received after the deadline will neither be considered nor evaluated.

To qualify you must have passed a PhD or equivalent. Applications will be assessed by an expert assessor/committee. Applicants will be informed of their assessment by the university.

The University wishes our staff to reflect the diversity of society and thus welcomes applications from all qualified candidates regardless of personal background.

Further information for international applicants about entering and working in Denmark.

About SDU

The University of Southern Denmark was established to create value for and with society. Whether our contributions come in the form of excellent research, innovative solutions, education or learning, we must make a positive difference to society and contribute to a sustainable future. We do this by cultivating talents and creating the best environments for research and learning. It is therefore crucial that SDU retains, develops and recruits talent. At the same time, we need to ensure consistently high quality in all our activities – and we can only do that with the right people. The University’s researchers, lecturers, students, managers and technical/administrative staff are the foundation of our success.

Location

Odense M, Denmark

Apply Before

2026-09-07T21:59:00+00:00