Postdoctoral Researcher in Data Science and Artificial Intelligence - BISS

Maastricht University (UM); Nederland; Sur place; EUR 55 000 - 75 000; Plein temps

Avantages offerts par ce poste

36 months contract

Competitive gross salary €4,925–€6,682

Flexible working hours

Résumé du poste

Maastricht University (UM) invites applications for a Postdoctoral Researcher in Data Science and Artificial Intelligence within the BISS at Maastricht University. The role focuses on developing multimodal AI methods to infer user states from neuro-physiological and behavioral data for adaptive VR training.

The successful candidate will lead the data science component of the three-year VR-STRESS project, collaborating across psychology, engineering, and VR development to publish results and

Qualifications

• PhD in data science, AI, ML, computer science, computational cognitive science, biomedical engineering, cognitive science, or related field.
• Experience developing and evaluating ML, statistical, or signal-processing methods for complex datasets.
• Comfort with scientific programming environments.

Responsabilités

• Lead the data science and artificial intelligence component of the VR-STRESS project.
• Develop methods for processing, integrating, and interpreting multimodal physiological and behavioral data.
• Investigate model interpretability, robustness, and generalizability; validate against self-reports and objective measures.
• Develop real-time or near-real-time algorithms for adaptive VR applications.
• Collaborate with experimental psychologists, cognitive scientists, engineers, and VR developers; disseminate results.

Connaissances

Data science

Machine learning

Multimodal sensing

Time-series analysis

Sensor fusion

Deep learning

Model interpretability

Cognitive science

Formation

PhD in data science / AI / ML / CS / cognitive science

Outils

Python

PyTorch

MATLAB

Description du poste

Psychological sciences » Behavioural sciences

Psychological sciences » Cognitive science

Computer science » Programming

Computer science » Cybernetics

Organisation/Company Maastricht University (UM) Research Field Engineering » Systems engineering Engineering » Biomedical engineering Psychological sciences » Behavioural sciences Psychological sciences » Cognitive science Computer science » Programming Computer science » Cybernetics Researcher Profile Recognised Researcher (R2) Application Deadline 4 Dec 2026 - 22:59 (UTC) Country Netherlands Type of Contract Temporary Job Status Not Applicable Hours Per Week 38.0 Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No

Offer Description

Welcome to Maastricht University!

Are you excited about developing AI methods that can make sense of complex human signals? Do you have a strong interest in machine learning, multimodal data, (neuro)physiological sensing, and adaptive systems? Are you fascinated by building sophisticated predictive models, but equally interested in understanding the mechanisms and human processes behind them? Then this postdoctoral position may be the one for you.

Postdoctoral Researcher in Data Science and Artificial Intelligence – BISS at Maastricht University.

• Our goal: Develop advanced multimodal AI methods that transform (neuro)physiological, behavioral, and interaction data into reliable indicators of user state, enabling adaptive and personalized VR training.
• Your colleagues: A collaborative and interdisciplinary team at BISS, where researchers from across Maastricht University work together to apply artificial intelligence and data science to societal and technological challenges.

We are looking for a postdoctoral fellow with a strong academic interest in data science, machine learning, artificial intelligence, and multimodal human sensing. The successful candidate will work on the three-year VR-STRESS project.

VR-STRESS is a cross-border research and innovation project aimed at developing an adaptive virtual reality system for medical training. The project investigates how (neuro)physiological, behavioral, and interaction data can be used to infer a user's cognitive and emotional state, and how these estimates can be translated into real-time adaptations of a virtual training environment.

A central component of the project is the development of an integrated system that combines multiple non-invasive sensing modalities and transforms raw data into meaningful indicators of stress, cognitive load, attention, fatigue, emotional state, and performance. A key scientific challenge is to combine heterogeneous physiological, neurophysiological, and behavioral signals into robust and interpretable models that work across individuals and changing conditions.

What you do

You will take a leading role in the data science and artificial intelligence component of the VR-STRESS project.

You will develop methods for processing, integrating, and interpreting multimodal physiological and behavioral data collected in controlled studies in which participants are exposed to different levels of stress, cognitive demand, and task complexity. Using signal processing, machine learning, and multimodal data-fusion techniques, you will investigate how patterns across different measurement channels can be used to estimate relevant aspects of user state.

A central scientific question is not only how accurately these states can be predicted, but also what the models can tell us about the signals and mechanisms underlying them. You will therefore study model interpretability, robustness, individual variability, and generalizability, and validate model outputs against subjective self-reports, experimental manipulations, behavioral measures, and objective performance indicators.

You will also contribute to the development of real-time or near-real-time methods that connect inferred user states to adaptive mechanisms in the VR environment. These mechanisms may, for example, dynamically adjust the intensity of stressors, task complexity, or the presentation of supportive information.

Your work will focus on:

• developing signal-processing, machine-learning, and multimodal data-fusion methods for heterogeneous human-sensing data;
• building and evaluating robust and interpretable models of cognitive, emotional, and physiological user states;
• translating these models into real-time or near-real-time algorithms for adaptive VR applications;
• collaborating closely with experimental psychologists, cognitive scientists, engineers, and VR developers, and disseminating results through scientific publications and conferences.

What you bring

We are interested in your expertise, scientific curiosity, and potential. You hold, or are close to completing, a PhD in data science, artificial intelligence, machine learning, computer science, computational cognitive science, biomedical engineering, cognitive science, mathematical psychology, or a related field. You have experience developing and evaluating machine-learning, statistical, or signal-processing methods for complex datasets, and you are comfortable working with different scientific programming environments.

You are interested in combining multiple data streams, including (neuro)physiological, behavioral, and interaction signals. Experience with time-series analysis, physiological signal processing, sensor fusion, deep learning, representation learning, or related approaches is particularly welcome.

We are looking for someone who enjoys building sophisticated models, but who also wants to understand why they work, what information they use, and how they relate to underlying psychological and physiological processes. An interest in virtual reality, adaptive systems, human-computer interaction, brain-computer interfaces, or physiological computing is therefore highly relevant.

We are particularly interested in candidates who:

• combine strong technical and quantitative skills with scientific curiosity about human cognition and physiology;
• are proactive and independent, while enjoying interdisciplinary collaboration;
• have a research track record appropriate to career stage and the ambition to publish in relevant scientific outlets;
• communicate fluently in written and spoken English. Knowledge of Dutch is welcome, but not required.

At BISS, you will work in an environment where artificial intelligence and data science are developed in close connection with societal and human questions. The VR-STRESS project therefore offers an opportunity not only to develop advanced AI methods, but also to investigate how these methods can contribute to intelligent systems that respond meaningfully to the people using them.

What we offer

At Maastricht University, you’ll work in an international, open, and engaged environment. We offer:

• An employment contract for a period of 36 months with a scope of 1.0 FTE.
• A gross monthly salary between €4925,00 and €6682,00 (based on full-time employment of 38 hours per week). 8% holiday allowance and an 8.3% year-end bonus.
• 29 vacation days (based on full-time), four additional days off (Carnival Monday and Tuesday, Good Friday, and Liberation Day), and the possibility to accrue up to 12 extra days through compensation hours.
• Flexible working hours, a home office allowance, and the option to work from home.
• Freedom and space to shape your work independently and develop your ideas.
• A close-knit community of colleagues to collaborate and grow with.
• A solid pension plan via ABP, company fitness schemes, and access to various university sports facilities.
• An inspiring work environment in the heart of Europe.

Faculty of Science and Engineering

At the Faculty of Science and Engineering (FSE), we focus on themes such as circularity and sustainability, future farming, digitisation and (scientific) instrument development. FSE's leading projects, like the Einstein Telescope Pathfinder, are sure to grab anyone's attention. The faculty is a vibrant hub of education and research in Science, Technology, Engineering, and Mathematics (STEM) and Liberal Arts and Sciences (LAS). At FSE, over 450 staff members and 3700 students gather to explore e exciting interdisciplinary research and educational programmes. Feel welcome, be part of our team and put your brilliant mind to work!

FSE at the Brightlands Campuses

Maastricht, Sittard-Geleen, Heerlen, and Venlo, the home of four creative Brightlands campuses, are bustling with 30,000 entrepreneurs, researchers, and students working diligently to solve global challenges. The Faculty of Science and Engineering is active on all four Brightlands campuses, and this is where our impact reaches its peak. To give you an idea of what is happening at each campus: Sittard-Geleen is home to the largest chemical site in the Euregion, while Venlo is a large hub for agri-food innovation. Maastricht is the site of the Health Campus, and Heerlen is the place to be for Smart Services.

Brightlands Institute for Smart Society (BISS)

At Brightlands Institute for Smart Society (BISS), Maastricht University scientists work on innovative and responsible solutions to data challenges. All disciplines and faculties collaborate in applying data science and technology to solve real life societal and business needs. BISS was set up by Maastricht University, the Province of Limburg and APG.

BISS is located on the Brightlands Smart Services Campus in Heerlen, the Netherlands.

BISS’ mission is to empower people and organisations through the socially responsible application of digital technologies. We focus on privacy preserving technologies, on value creation from data, and on human-technology interaction.

BISS is part of Brightlands, an open innovation community in Limburg, The Netherlands with 29,000 innovative entrepreneurs, researchers and students. Every day they work on breakthroughs in the field of sustainability, health and digitization. At Brightlands Smart Services Campus in Heerlen they enable knowledge in the field of data science to lead to new smart digital services that improve the quality of life.

Interested?

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