PhD Position in Machine Learning for Scientific Inference in Behavioural Science at Leiden University

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TaibaTahir
February 12, 2026 (Updated March 13, 2026) 5 min read

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Leiden University – Leiden, Netherlands
Application Deadline: 13 March 2026
Start Date: 16 April 2026
Supervisor: Dr. Marjolein Fokkema
Vacancy Number: 16386
Employment: Full-time (38 hours per week)

Overview

Leiden University is offering a fully funded PhD position in Machine Learning for Scientific Inference within the field of Behavioural Science. This research opportunity focuses on advancing interpretable machine learning, statistical methodology, and meta-analysis to improve the scientific value and generalizability of machine learning results in psychology and behavioural research.

The project is funded by the Dutch Research Council (NWO) and led by Dr. Marjolein Fokkema, Associate Professor in Methodology and Statistics for Psychology.

Research Focus: Machine Learning, Statistics, and Behavioural Science

Machine learning (ML) enables highly flexible modeling of complex, high-dimensional behavioural data. However, ML models often lack interpretability, valid effect size estimation, and uncertainty quantification, which limits their scientific applicability.

This PhD project aims to bridge the gap between machine learning and scientific inference by developing:

  • Statistically valid and interpretable effect size measures for ML models

  • Accurate uncertainty estimation methods

  • Machine learning-based meta-analysis techniques for combining and comparing results across studies

  • Generalizable frameworks for reproducible behavioural science research

The research sits at the intersection of:

  • Statistical learning

  • Artificial intelligence

  • Bayesian regression methods

  • High-dimensional data analysis

  • Meta-analytic methodology

  • Open science practices

Key Responsibilities

As a PhD candidate in statistical methods and machine learning, you will:

  • Develop novel statistical methodology for interpretable machine learning

  • Implement methods in open-source software (primarily in R)

  • Conduct Monte Carlo simulation studies to validate new approaches

  • Apply methods to real-world behavioural science datasets

  • Publish research in peer-reviewed scientific journals

  • Present findings at national and international conferences

  • Collaborate with interdisciplinary researchers in psychology and related fields

  • Contribute to software documentation, tutorials, and methodological guidance

  • Participate in advanced courses and workshops within the Graduate School of Social and Behavioural Sciences

Research Environment

Faculty of Social and Behavioural Sciences

Leiden University’s Faculty of Social and Behavioural Sciences includes five institutes:

  • Centre for Science and Technology Studies

  • Cultural Anthropology and Development Sociology

  • Education and Child Studies

  • Political Science

  • Psychology

The faculty hosts approximately 7,000 students and 1,000 staff members and is internationally recognized for high-impact research on human behaviour and societal structures.

Institute of Psychology

The Institute of Psychology focuses on research themes including:

  • Health and Wellbeing

  • Social, Cognitive, and Affective Decision Making

  • Development and Learning

  • Advanced Behavioural Science Methods

The institute emphasizes:

  • Interdisciplinary collaboration

  • Open science and research transparency

  • Inclusivity and academic integrity

  • Innovation in research methodology

With approximately 5,000 students and 600 staff members, it provides a dynamic academic environment for doctoral research.

Methodology and Statistics Unit

The PhD candidate will join the Methodology and Statistics Unit, which specializes in:

  • Neuroimaging statistics

  • Statistical learning and artificial intelligence

  • Applied psychometrics and sociometrics

  • Responsible research methods

The unit offers a collaborative, international research team committed to rigorous statistical methodology and open science.

Candidate Profile

Required Qualifications

  • Completed research Master’s degree in statistics, data science, psychology, or a related quantitative discipline

  • Strong programming skills in R

  • Experience with data analysis and Monte Carlo simulations

  • Excellent written and spoken English

  • Strong analytical and communication skills

  • Demonstrated interest in behavioural science research

Preferred Qualifications

  • Background in Bayesian regression and high-dimensional modeling

  • Knowledge of interpretable machine learning methods

  • Experience with meta-analysis techniques

  • Experience developing statistical methods or statistical software

Candidates who do not meet every requirement but demonstrate strong motivation and research potential are encouraged to apply.

Employment Conditions and Benefits

This PhD position is offered under the Collective Labour Agreement of Dutch Universities.

Contract Details

  • Full-time position (38 hours per week)

  • Initial 1-year contract, extendable to 4 years upon positive evaluation

  • Monthly gross salary: €3,059 – €3,881 (based on full-time appointment)

Additional Benefits

  • 8% holiday allowance

  • 8.3% end-of-year bonus

  • Pension scheme through ABP

  • Full reimbursement of public transport commuting costs

  • Minimum of 29 leave days per year (based on 38-hour work week)

  • Flexible working hours and options for additional leave accrual

  • Hybrid working within the Netherlands

  • Home-working allowance (internet and remote work compensation)

  • Laptop and mobile phone provided

  • Access to university wellbeing initiatives and professional development programs

Leiden University also supports:

  • Paid parental leave

  • Sabbatical options

  • Individual employment benefits exchange programs

  • Sports and bicycle schemes

Commitment to Diversity and Inclusion

Leiden University promotes an inclusive academic community where diversity of perspectives strengthens research and education. The university values equity, open science, and a safe working environment where all staff and students can reach their full potential.

Application Procedure

  • Application deadline: 13 March 2026

  • Interview period: 14–24 March 2026

  • Project start date: 16 April 2026

Applications are reviewed on a rolling basis.

The selection process may include reference checks, diploma verification, and a certificate of good conduct (VOG).

In case of equal suitability, preference will be given to internal candidates.

Why Apply for This PhD in Machine Learning and Behavioural Science?

This position offers a unique opportunity to:

  • Advance interpretable machine learning in scientific research

  • Contribute to cutting-edge statistical methodology

  • Work at a top European research university

  • Develop expertise in meta-analysis and uncertainty quantification

  • Publish impactful research at the intersection of AI and psychology

If you are passionate about statistical learning, behavioural data science, and improving the scientific rigor of machine learning, this PhD position at Leiden University offers an exceptional research environment to launch your academic career.

Apply now at : PhD position in machine learning for scientific inference for behavioural science Job Details | Universiteit Leiden

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Written by TaibaTahir Published on February 12, 2026
Sweden

PhD Position in Environmental Technology and Management at Linköping University

🏛️ Linkoping University 📍 Sweden 📚 Business Administration Open · 32 days left (Deadline: May 31, 2026)
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Taiba Tahir
April 29, 2026 (Updated April 28, 2026) 3 min read

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Position Overview

Linköping University is offering a PhD position in Environmental Technology and Management at the Department of Business Administration in Sweden. The position is part of the Division of Environmental Technology and Management (MILJÖ), focusing on sustainable production systems and circular economy transitions in manufacturing industries. The start date is September 2026, with applications open until 31 May 2026.

Research Focus

The PhD project investigates how manufacturing industries transition from linear production models to circular and sustainable systems, with a specific focus on remanufacturing and closed-loop production systems (CLPS).

Key research themes include:

  • Development and scaling of remanufacturing in industry

  • Circular economy strategies in manufacturing systems

  • Economic sustainability of product lifecycle extension

  • Integration of remanufacturing into production and supply chains

  • Innovation in technologies supporting circular manufacturing

The research is conducted within two ongoing projects:

  • ROAR project (resource-efficient and resilient recirculation of products and components)

  • Innovate Remanufacturing project (technology-driven innovation in remanufacturing processes)

Responsibilities

The PhD candidate will:

  • Participate in theoretical and empirical research projects

  • Collect, structure, and analyze qualitative and quantitative data

  • Conduct interviews and develop case studies with Swedish manufacturing companies

  • Design research methods, frameworks, and analytical models

  • Contribute to academic publications and presentations

  • Support ongoing research collaborations with industry and academic partners

  • Communicate findings in both written and oral form

  • Assist with teaching or departmental duties (up to 20% of workload)

Candidate Requirements

Applicants must have a Master’s degree (or equivalent, including near completion) in one of the following areas:

  • Sustainability Engineering and Management

  • Industrial Engineering and Management

  • Mechanical Engineering

  • Or closely related technical or management disciplines

Essential requirements include:

  • Strong understanding of scientific research methods

  • Ability to collect, structure, and analyze research data systematically

  • Experience with interviews, qualitative analysis, or case study research

  • Good written and spoken English skills

Preferred Qualifications

The following are considered advantageous:

  • Knowledge of manufacturing systems and production economics

  • Understanding of circular economy and sustainability strategies

  • Documented interest in sustainable or circular manufacturing systems

  • Basic knowledge of Swedish (merit, not required)

Work Environment

The position is hosted at the Division of Environmental Technology and Management (MILJÖ), an interdisciplinary research group with around 40 researchers from diverse academic and cultural backgrounds.

The division focuses on:

  • Environmental innovation

  • Sustainable product and system development

  • Industrial transformation toward resource efficiency

  • Collaboration with industry and society

The PhD candidate will work within the Products, Services, Innovation (PSI) unit, engaging in applied and theoretical sustainability research.

PhD Structure

The position is a doctoral research role with:

  • Initial employment of 1 year, extendable based on progress

  • Total duration of up to 2 years full-time equivalent (with possible extensions depending on teaching or duties)

  • Formal admission to Linköping University’s PhD programme required after hiring

The role begins in September 2026.

Salary and Benefits

  • Competitive PhD salary with structured progression

  • Employment within a leading Swedish research university

  • Access to interdisciplinary and international research networks

  • Opportunity to collaborate with industry partners

  • Support for academic development and research dissemination

  • Inclusive and diverse working environment

Application Requirements

Applicants must submit:

  • CV

  • Cover letter explaining motivation and research interests

  • Academic transcripts and Master’s degree documentation

  • Description of relevant scientific experience and methods

  • Any publications or research outputs (if available)

  • Contact details of referees

Applications must be submitted via Linköping University’s official system before 1 June 2026. Late applications will not be considered.

Additional Information

The university emphasizes equal opportunity, diversity, and inclusion in recruitment. Applicants from all backgrounds are encouraged to apply.

For further information, candidates may contact Professor Erik Sundin or the departmental staff listed in the announcement.

TT
Written by Taiba Tahir Published on April 29, 2026
Norway

PhD Candidate in Cancer Neuroscience at NTNU

TT
Taiba Tahir
April 29, 2026 (Updated April 28, 2026) 3 min read

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Position Overview

The Norwegian University of Science and Technology (NTNU) is offering a 3-year PhD position in Cancer Neuroscience at the Department of Clinical and Molecular Medicine in Trondheim, Norway. The position is part of the research group led by Dr. Nathalie Jurisch-Yaksi and focuses on understanding brain–tumor interactions in glioblastoma.

Research Focus

This PhD project investigates how glioblastoma cells interact with and exploit the brain environment to grow, survive, and invade. The research combines cancer biology and neuroscience using advanced experimental models.

A key component of the project involves:

  • Zebrafish xenograft models using patient-derived glioma cells

  • Study of tumor–brain interactions in vivo

  • Analysis of cancer progression in neural environments

The project integrates molecular biology, neuroscience, and computational analysis to understand tumor behavior in the brain.

Key Research Methods

The candidate will work with a wide range of experimental and computational techniques, including:

  • Molecular and cellular biology

  • Cell culture and primary cell systems

  • Immunohistochemistry and histology

  • Advanced imaging and microscopy

  • Zebrafish experimental models and behavioral assays

  • Genetics and brain activity analysis

  • Programming and data analysis (Python, MATLAB, or similar tools)

Responsibilities

The PhD candidate will:

  • Complete doctoral training leading to a PhD degree

  • Conduct high-quality, reproducible research

  • Contribute to scientific publications and outreach activities

  • Participate in international collaborations, workshops, and conferences

  • Supervise and mentor students at bachelor’s, master’s, and PhD levels

  • Contribute to teaching and academic development within the research group

  • Adapt to evolving research needs during the project

Candidate Requirements

Applicants must have a strong academic background in neuroscience and a completed Master’s degree in Neuroscience (or equivalent).

Essential requirements include:

  • Strong academic performance (minimum grade B or equivalent)

  • Eligibility for admission to the NTNU PhD programme in Medicine and Health Sciences

  • Excellent written and spoken English skills

  • Certification for animal experimentation (FELASA or Norwegian equivalent)

  • Proven experience with zebrafish research

  • Experience with cell culture, including primary cells

  • Laboratory skills in immunohistochemistry and imaging

  • Programming skills in Python, MATLAB, or equivalent

Preferred Qualifications

Additional experience considered advantageous includes:

  • Molecular and cellular neuroscience techniques

  • Imaging and immunostaining expertise

  • Image analysis tools such as Python or Imaris

  • Experience measuring animal behavior or brain activity

  • Prior neuroscience research experience

Personal Competencies

The ideal candidate should be able to:

  • Work independently and collaboratively in interdisciplinary teams

  • Plan, structure, and execute research effectively

  • Demonstrate curiosity and strong motivation for neuroscience research

  • Analyze complex data and draw evidence-based conclusions

  • Adapt flexibly to evolving project directions

PhD Programme Structure

The position is part of NTNU’s structured PhD programme in Medicine and Health Sciences. Candidates must gain formal admission within three months of starting.

The employment duration is 3 years and requires full-time presence at NTNU in Trondheim.

Salary and Benefits

  • Annual salary: NOK 550,800 (approximate, depending on experience)

  • Membership in the Norwegian Public Service Pension Fund

  • Career development and academic mentoring

  • Participation in an international research environment

  • Free Norwegian language training (A2 level)

  • Access to employee welfare and institutional benefits

  • Structured guidance throughout the PhD period

Application Requirements

Applicants must submit:

  • Motivation letter

  • CV

  • Bachelor’s and Master’s transcripts and diplomas

  • Copy of Master’s thesis

  • One-page research plan focusing on zebrafish xenograft studies

  • Publications or relevant academic work (if available)

  • Certificates (if applicable)

  • Contact details for three referees

  • Documentation for international education (if applicable)

Applications must be submitted through NTNU’s official Jobbnorge portal.

Deadline

15 May 2026

Additional Information

For academic inquiries, contact Dr. Nathalie Jurisch-Yaksi. For recruitment questions, contact NTNU HR staff.

NTNU promotes diversity, inclusion, and equal opportunity in recruitment and encourages applications from candidates of all backgrounds.

TT
Written by Taiba Tahir Published on April 29, 2026
Germany

PhD Position in Computer Science at Technical University of Munich

TT
Taiba Tahir
April 29, 2026 (Updated April 28, 2026) 3 min read

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Position Overview

The Technical University of Munich (TUM) is offering a fully funded PhD position in Computer Science at the Institute for AI and Informatics in Medicine (AIIM). The position is part of the xMDT-HPB project, focusing on artificial intelligence for precision oncology, medical informatics, and explainable multimodal AI systems. The role is based in Munich, Germany and is supervised by Dr. Felix Busch.

Research Project: xMDT-HPB

The xMDT-HPB project develops an explainable and interoperable AI system to improve diagnosis and treatment decisions for patients with hepato-pancreato-biliary cancers. The project integrates multiple clinical data sources, including:

  • Medical text and clinical narratives

  • Radiological imaging data

  • Laboratory and patient trajectory data

The goal is to build trustworthy AI systems that support clinicians in personalized prognosis and treatment planning. All outputs are designed as open-source software and reusable research tools.

Key Responsibilities

The selected PhD candidate will:

  • Conduct doctoral research within the xMDT-HPB project under structured supervision

  • Work with clinical data and medical informatics standards such as MII and FHIR

  • Develop and implement prototypes for explainable, multimodal AI systems

  • Design and evaluate machine learning models for text, imaging, and structured clinical data

  • Build reproducible ML pipelines and benchmarking frameworks

  • Collaborate with clinicians, data scientists, and software engineers

  • Contribute to scientific publications, conferences, and project reports

  • Support open-source development and technical documentation

Candidate Requirements

Applicants should have a Master’s degree (or near completion) in one of the following fields:
Computer Science, Medical Informatics, Data Science, Bioinformatics, or a related discipline.

Required qualifications include:

  • Strong programming skills in Python

  • Basic experience with ML frameworks such as PyTorch or TensorFlow

  • Prior experience in machine learning, NLP/LLMs, data analysis, or software development

  • Interest in medical AI, clinical data, and interdisciplinary research

  • Willingness to work with medical standards and data protection regulations

  • Strong teamwork and communication skills

  • Good written and spoken English

  • German language skills at C1 level (required for clinical collaboration)

Applicants should also provide evidence of past projects, GitHub/GitLab links (if available), and academic outputs such as theses or publications.

PhD Structure and Work Environment

The position is a structured doctoral role at TUM with close academic supervision. The candidate will work in an interdisciplinary environment combining:

  • Artificial intelligence research

  • Medical informatics

  • Clinical oncology applications

The research emphasizes reproducibility, open science, and collaboration with healthcare professionals.

Salary and Benefits

  • Full-time PhD position funded under TV-L E13 pay scale

  • Occupational pension scheme (VBL)

  • Structured academic supervision and mentoring

  • Support for conference participation and scientific publishing

  • Access to qualification programs and career development

  • Open-source research contributions

  • Employee benefits including Wellpass and university services

  • Workplace located in central Munich (Max-Weber-Platz)

Application Requirements

Applicants must submit a single PDF including:

  • Motivation letter

  • CV

  • Academic transcripts and certificates (Bachelor’s and Master’s)

  • Overview of programming or ML projects (GitHub/GitLab optional)

  • List of publications or academic work (if available)

  • Contact details of two academic referees

Applications should be sent directly to Dr. Felix Busch. Applications are reviewed on a rolling basis until the position is filled.

Additional Information

This position is suitable for candidates with disabilities, who will be given preference in case of equal qualification. The university emphasizes equal opportunity and inclusive hiring practices.

For further details, candidates may contact Dr. Felix Busch at the Institute for AI and Informatics in Medicine, TUM School of Medicine and Health, Munich.

TT
Written by Taiba Tahir Published on April 29, 2026
Norway

PhD Position in Political Science at University of Bergen

🏛️ University of Bergen 📍 Norway 📚 Political Science Open · 61 days left (Deadline: June 29, 2026)
TT
Taiba Tahir
April 29, 2026 (Updated April 28, 2026) 3 min read

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Position Overview

The University of Bergen is offering a 3-year PhD position in Political Science within the Department of Government and the Centre for Research on Discretion and Paternalism. The role is part of the PROTECT research project on child rights and crime prevention. The position starts on 1 January 2027 and is based in Bergen, Norway.

Research Project: PROTECT

PROTECT (Protecting Child Rights and Public Safety) is a five-year interdisciplinary research project funded by the Research Council of Norway. It examines how welfare states can respond to children involved in serious violent crime while balancing:

  • Protection of child rights

  • Public safety and crime prevention

  • Social inclusion and prevention of exclusion

The project focuses on child protection systems and criminal justice systems, using comparative and interdisciplinary approaches. The PhD candidate will primarily contribute to work packages 3 and 4.

Centre for Research on Discretion and Paternalism

The PhD is hosted at a leading research centre focused on how governments exercise power and justify interventions in citizens’ lives. The centre conducts comparative research on welfare states, child protection, and governance, and collaborates internationally with law, sociology, political science, and psychology scholars.

PhD Responsibilities

The selected candidate will:

  • Conduct independent academic research leading to peer-reviewed publications

  • Collect and analyze quantitative and comparative data

  • Collaborate with project leaders and international partners

  • Contribute to research activities at the centre

  • Participate actively in the PROTECT project environment

Candidate Requirements

Applicants must have:

  • A Master’s degree in Political Science or Sociology (grade B or higher required)

  • Strong expertise in quantitative research methods

  • Interest in child rights, welfare systems, or crime prevention

  • Ability to work independently and collaboratively

  • Excellent English skills (written and spoken)

  • Knowledge of a Scandinavian language (advantage)

  • Relevant research experience (advantage)

Selection will be based on academic performance, methodological strength, and the quality and fit of the research proposal.

PhD Programme Structure

The position is part of the PhD programme at the Faculty of Social Sciences, University of Bergen. It is a 3-year research training position leading to a PhD degree.

Applicants must submit a research proposal that includes:

  • Research topic and questions

  • Theoretical framework

  • Methodological approach

  • Work plan and timeline

  • Alignment with PROTECT work packages 3 and 4

Admission depends on approval of the proposal.

Salary and Benefits

  • Annual salary: NOK 568,700

  • Automatic annual salary increases (3% per year)

  • Membership in the Norwegian Public Service Pension Fund

  • Strong international research environment

  • Collaboration with leading academic networks

  • Good welfare benefits

Application Requirements

Applicants must submit:

  • Cover letter with motivation and research interests

  • Research proposal (max 3 pages, excluding references)

  • CV including education and research experience

  • Academic transcripts and diplomas

  • Master’s thesis or relevant academic work

  • Contact details for two referees

Applications must be submitted via Jobbnorge. Applications without a research proposal will not be considered.

Deadline

30 June 2026

Additional Information

For academic questions, contact the principal investigator. For administrative guidance or PhD programme queries, contact the University of Bergen’s designated staff.

The University of Bergen encourages applications from diverse backgrounds and promotes equal opportunity in recruitment.

TT
Written by Taiba Tahir Published on April 29, 2026