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Pedro Cardoso-Leite

4 months ago

PhD candidate in AI and cognitive sciences University of Luxembourg in Luxembourg

Degree Level

PhD

Field of study

Neuroscience

Funding

Available

Deadline

Jul 1, 2026

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Country

Luxembourg

University

University of Luxembourg

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Keywords

Neuroscience
Computer Science
Data Science
Psychology
Cognitive Science
Signal Processing
Deep Learning
Artificial Intelligence
Open Science
Software Engineering
Python Programming
Eeg
Experimental Psychology
R Programming
Applied Behavior Analysis
Computational Modelling
Statistic
Machine learning

About this position

The University of Luxembourg, a leading international research university, is seeking a PhD candidate in AI and cognitive sciences to join the dynamic xCIT research group within the Faculty of Humanities, Education and Social Sciences (FHSE). The xCIT group specializes in developing and applying digital technologies to study and improve human lives, with research spanning learning enhancement, mental health, green skills, and cybersecurity. As part of the Department of Behavioral and Cognitive Science, the group offers a rich interdisciplinary environment, integrating expertise from cognitive science, psychology, computer science, and data science. The successful candidate will contribute to the development of computational models and data analysis pipelines for large, multimodal behavioral datasets, employing both traditional statistical methods and modern machine learning approaches such as deep learning. The research aims to advance explainable computational models of human behavior and cognition. The position involves conducting innovative research, publishing and presenting findings internationally, participating in a structured PhD training plan, and engaging in collaborative and outreach activities within the group and university. Applicants should have a Master's degree in a relevant field (Computer Science, Data Science, Experimental Psychology, Cognitive Science), with demonstrated experience in data processing, programming (Python/R), computational modeling, and statistics. Familiarity with experimental psychology, cognitive neuroscience, and technical skills in machine learning, deep learning, and optionally bio-signal processing (EEG, BCI) are desirable. Strong communication skills in English, organizational ability, and a collaborative, inquisitive mindset are essential. The University offers a modern, international environment with high-quality equipment, strong industry ties, and a commitment to inclusivity and open science. The position is a fixed-term, full-time contract for 36 months, based at Campus Belval, with a planned start date in September 2025. The annual gross salary is EUR 40952. Applications should be submitted online, including a CV, cover letter, portfolio, diploma certificates, and referee contacts. Early applications are encouraged, with a deadline of July 1, 2025.

Funding details

Available

What's required

Applicants must hold a Master's degree in Computer Science (with a focus on AI), Data Science, or related fields; or Experimental Psychology, Cognitive Science, or related disciplines. Required experience includes data processing, data analysis, programming, computational modeling, and statistics. Familiarity with research methods in experimental psychology and cognitive neuroscience (e.g., empirical research, experiment design, questionnaire, EEG) is expected. Technical skills in Python and/or R, data science (tidyverse, pandas), machine learning (scikit-learn), deep learning (PyTorch, Keras3), and optionally bio-signal processing and brain imaging (EEG, BCI) are desired. Software engineering methodologies and tools (GitHub, Markdown, LaTeX, DVC) are advantageous. Proficiency in written and oral English is required; French is an advantage. Candidates should demonstrate strong organizational skills, teamwork, scientific curiosity, open-mindedness, and research integrity.

How to apply

Apply online through the University of Luxembourg HR system by submitting a detailed CV (with links to work samples), a cover letter (max 1 page), portfolio, writing and work samples, digital copies of diploma certificates, and names/contact details of two academic referees. Early application is encouraged as applications are processed upon reception. Applications by email will not be considered.

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