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University of Warsaw

PhD Student (Research Assistant) in Topological Data Analysis for Trustworthy AI University of Warsaw in Poland

Degree Level

PhD

Field of study

Computer Science

Funding

Available

Deadline

Nov 19, 2026

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Country

Poland

University

University of Warsaw

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Keywords

Computer Science
Deep Learning
Mathematics
Artificial Neural Network
Computational Geometry
High-dimensional Data
Physics
Applied Mathematic
ML

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About this position

PhD Student (Research Assistant) position at the Center of Trustworthy AI for Life Sciences – International Research Agendas Programme, University of Warsaw

This PhD opening is part of the Center of Trustworthy AI for Life Sciences (TRAILS) at the University of Warsaw, in Warsaw, Poland. The project sits at the intersection of applied mathematics and computer science, with a strong focus on topological data analysis (TDA) and trustworthy artificial intelligence.

The successful candidate will work on mathematical and algorithmic methods for understanding how artificial neural networks function, especially by studying the geometry and topology of activation spaces and internal representations. The research includes analyzing how representations evolve during training and how these changes relate to prediction quality, generalization, robustness, and adversarial behavior.

Planned work involves developing and implementing computational tools based on Mapper, Ball Mapper, and persistent homology, and applying them to convolutional neural networks, Transformer-based models, and other modern architectures. The project also includes designing computational experiments on real-world and synthetic data, with opportunities to investigate anomalous model behavior and adversarial examples.

The role is suitable for a strong candidate with a background in mathematics, computer science, data science, physics, or a related field. The advertised requirements emphasize a Master’s degree or equivalent, solid preparation in machine learning, TDA, applied topology, computational geometry, dynamical systems, or mathematical data analysis, strong Python programming skills, and the ability to work independently and communicate research clearly in English. The candidate must be a current PhD student or be admitted to a doctoral program.

Applications should be submitted in English and should include a cover letter, scientific CV with publications and experience, a description of key competencies, a description of scientific achievements, the Applicant Questionnaire form, and a scan of the Master’s diploma. The completed application package must be sent by email to [email protected], quoting reference number TRAILS-1210-12/2026. The deadline is 19 November 2026 at 16:00 (Europe/Warsaw).

This is a temporary part-time position (20 hours per week). The post is associated with the University of Warsaw and offers a research environment focused on interdisciplinary collaboration, mathematical foundations of AI, and experimental computational research.

Funding details

Available

What's required

Applicants should have a Master’s degree or equivalent in mathematics, computer science, physics, data science, or a related discipline appropriate to the career stage. A strong background in at least one of machine learning, Topological Data Analysis, applied topology, computational geometry, dynamical systems, or mathematical data analysis is expected, ideally with industrial experience. Candidates should be familiar with the basic principles of machine learning and neural networks, have strong programming skills preferably in Python, be able and willing to work with high-dimensional data and computational models, work independently, formulate research questions, communicate results clearly, and have a good command of written and spoken English. The candidate must be a PhD student in a doctoral program or already admitted to one. Additional assets include experience with persistent homology, Mapper, Ball Mapper, deep neural networks, PyTorch/TensorFlow/JAX, convolutional neural networks, transformers, adversarial examples, robustness, interpretability, dynamical systems, dimensionality reduction, manifold learning, clustering, NLP, or interdisciplinary/industrial collaboration.

How to apply

Prepare a single PDF or ZIP file containing the required documents, including the cover letter, CV, competencies and achievements descriptions, Applicant Questionnaire, and a scan of the Master’s diploma. Email the application to [email protected] and include the reference number TRAILS-1210-12/2026 in the subject line. Applications must be submitted by 19 Nov 2026 at 16:00 Warsaw time.

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