University: Norwegian University of Science and Technology Location: Trondheim, Norway Supervisor: Samita Giri – samita.giri@ntnu.noDeadline: April 7, 2026

About NTNU

The Norwegian University of Science and Technology (NTNU) is a leading technical and scientific university with campuses in Trondheim, Ålesund, and Gjøvik. With over 43,000 students and 9,000 employees, NTNU works under the vision “Knowledge for a better world,” combining research excellence with societal impact.

About the PhD Position

The Faculty of Medicine, Department of Neuromedicine and Movement Science (INB), invites applications for a 3-year full-time PhD position in registry-based migraine research. The candidate will join the research group Understanding Headache Through Registry Data at the Norwegian Centre for Headache Research (NorHead). The position is funded by NTNU and the Central Norway Health Authority (Samarbeidsorganet). You will work in an interdisciplinary and international environment alongside PhD candidates, postdoctoral fellows, and senior researchers. The immediate leader is Trine Aakvik Strand.

Research Project Overview

Chronic migraine is a leading cause of disability worldwide, placing a major burden on patients and healthcare systems. The introduction of anti-CGRP monoclonal antibodies (mABs) has significantly changed migraine prevention strategies. However, key questions remain regarding:

• Optimal treatment duration

• Outcomes after discontinuation

• Effects of treatment reinitiation

This PhD project will evaluate how anti-CGRP mABs influence acute migraine medication use across different treatment phases — initiation, discontinuation, and reinitiation. Using comprehensive nationwide Norwegian registry data, the research will generate real-world evidence on treatment effectiveness. The findings will support clinical decision-making, improve treatment strategies, and enhance care for patients with chronic migraine. The project includes collaboration with leading research groups in the UK, Denmark, and Spain, including the High-Dimensional Neurology Group at UCL Queen Square Institute of Neurology in London.Duties and Responsibilities

• Conduct high-quality registry-based research

• Contribute to shaping and advancing the project

• Complete doctoral education and obtain a PhD degree

• Publish in peer-reviewed journals and engage in science communication

• Participate in research meetings and international conferences

• Collaborate with interdisciplinary and international partners

Required Qualifications

Applicants must have:

• A Master’s degree (or equivalent) in medicine, pharmacology/pharmacy, public health, epidemiology, statistics, biostatistics, or machine learning/AI

• Strong academic performance (equivalent to grade B or better on NTNU’s scale)

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

• Proficiency in written and spoken English

Preferred Qualifications

• Experience working with registry data or large datasets

• Knowledge of advanced statistical methods, time series analysis, or machine learning applications

• Proficiency in statistical software such as STATA, R, Python, or SAS

Personal Characteristics

The ideal candidate demonstrates:

• Strong motivation for headache research and public health

• Independent and structured working style

• Excellent collaboration skills

• Resilience and adaptability

• Initiative and flexibility in research planning

Salary and Employment Conditions

• Position code 1017 (PhD Candidate)

• Gross annual salary: NOK 550,800 (subject to qualifications and seniority)

• 3-year employment period

• Membership in the Norwegian Public Service Pension Fund

• Access to NTNU employee benefits and career development support

Admission to the organized PhD programme is required within three months of starting the position.

Application Requirements

Applications must be submitted electronically and include:

• 1–2 page motivation letter

• CV

• Bachelor’s and Master’s transcripts and diplomas

• Copy of Master’s thesis (or draft if recently submitted)

• Publications or relevant research work (if applicable)

• Contact information for three referees

All documents must be in English.

Why Apply?

This PhD opportunity at NTNU offers the chance to conduct impactful registry-based migraine research, contribute to improving chronic migraine treatment strategies, and collaborate within an internationally recognized headache research environment in Trondheim — one of Norway’s leading academic and technological cities. For further information, contact Samita Giri at samita.giri@ntnu.no. Apply now at: https://www.jobbnorge.no/en/available-jobs/job/296638/phd-candidate-in-registry-based-research-on-migraine-treatment-and-outcomes

The University of Luxembourg is offering a fully funded PhD position in Artificial Intelligence and Autonomous Driving Systems at the Interdisciplinary Centre for Security, Reliability and Trust (SnT). This doctoral opportunity is part of the European research project AutHUMate, focusing on human-centered AI systems for advanced driver assistance and automated driving technologies.

The position is based in Luxembourg City and provides a strong international research environment in collaboration with academic and industry partners.

Overview of PhD Position

• Level of Study: PhD (Doctoral Researcher)

• Institution: University of Luxembourg

• Centre: SnT – Interdisciplinary Centre for Security, Reliability and Trust

• Research Group: UBIX Research Group

• Supervisor: Prof. Raphaël Frank

• Study Location: Kirchberg Campus, Luxembourg City

• Duration: 36 months (fixed-term contract)

• Salary: €41,976 per year (gross, full-time)

• Language Requirement: English (minimum B2 level)

Project Overview

This PhD is part of the AutHUMate European project, which focuses on improving interaction between humans and automated driving systems.

The research will explore:

• Adaptive human-centered AI systems for driving assistance

• Driver behavior and readiness detection using multimodal data

• Trust modeling in autonomous driving systems

• AI-based communication strategies for driver-vehicle interaction

• Simulation and real-world testing of automated driving systems

The candidate will contribute to both theoretical research and practical implementation, including open-source software development and validation experiments.

Research Environment

The selected PhD candidate will join the UBIX Research Group at SnT, one of Europe’s leading ICT research centers.

SnT is known for its strong industry collaboration in areas such as:

• Autonomous systems

• Cybersecurity

• Machine learning

• Robotics

• Satellite systems

• Cloud computing

• Vehicular networks

The center works closely with European institutions, private companies, and government organizations.

Required Profile

Applicants should meet the following criteria:

Education

• MSc degree (or equivalent) in:

  • Computer Science

  • Electrical Engineering

  • Robotics

  • Artificial Intelligence

  • Related engineering fields

Technical Skills (preferred)

• Automated driving systems

• Machine learning

• Computer vision

• Vision-language models

• Robotics

• Control systems

• Communication systems

Language

• English proficiency at B2 level or higher

Key Responsibilities

The PhD researcher will:

• Conduct research in AI-driven autonomous driving systems

• Publish findings in scientific journals and conferences

• Collaborate with international academic and industry partners

• Develop and share open-source software tools

• Contribute to project integration and reporting

Salary and Benefits

This is a fully funded PhD position offering:

• Annual salary of €41,976 (gross)

• Full-time employment contract (3 years)

• Access to advanced research infrastructure

• International collaboration opportunities

• Participation in EU-funded research projects

• Supportive academic and multicultural environment

Required Application Documents

Applicants must submit:

• Curriculum Vitae (CV), including:

  • Education details (degree, institution, dates)

  • Thesis summary

  • Publications (if any)

• Cover letter explaining motivation and research fit

• Academic transcripts

• Contact details of at least two referees

• GitHub or portfolio link (if available)

How to Apply

To apply for this PhD position:

1. Submit your application through the official online HR system

2. Include all required documents in a single application

3. Applications sent via email are not accepted

4. Early applications are strongly encouraged as selection is continuous

Contract Details

• Position Title: Doctoral Researcher

• Contract Type: Fixed-term (36 months)

• Working Hours: Full-time (40 hours/week)

• Campus: Kirchberg, Luxembourg

About SnT (University of Luxembourg)

The Interdisciplinary Centre for Security, Reliability and Trust (SnT) is a leading European research center focused on:

• Secure and intelligent ICT systems

• AI and machine learning

• Autonomous systems and robotics

• Industry-driven innovation projects

SnT collaborates with top global institutions and industry partners, making it one of Europe’s most competitive research environments.

Why Apply for This PhD?

This position is ideal for candidates who want to:

• Work on cutting-edge AI and autonomous driving research

• Join a top European research center

• Collaborate with industry and academia

• Contribute to real-world AI systems in transportation

• Build a strong research career in Europe

The University of Luxembourg is inviting applications for fully funded PhD positions in Finance at the Faculty of Law, Economics and Finance (FDEF). These doctoral roles are designed for highly motivated candidates with strong quantitative backgrounds who want to pursue advanced research in economics, finance, and econometrics in Europe.

The program follows an international PhD structure, including rigorous coursework in the first year and several years of dedicated research leading to a doctoral thesis.

Overview of University of Luxembourg PhD Program

• Level of Study: PhD (Doctoral Researcher)

• Institution: University of Luxembourg

• Faculty: Faculty of Law, Economics and Finance (FDEF)

• Study Location: Luxembourg City, Luxembourg

• Campus: Belval Campus

• Duration: 3 years (fixed-term contract)

• Annual Salary: €41,976 (gross, full-time)

• Language: English (minimum B2 level required)

Program Structure

The PhD in Finance at the University of Luxembourg is structured in two phases:

• Year 1: Coursework equivalent to the Master in Quantitative Economics and Finance (MQEF)

• Years 2–5: Independent research leading to a doctoral dissertation

Courses are taught in English by faculty members and visiting scholars from top global universities such as Princeton and the University of Chicago.

Research Environment

The Department of Finance is located in Luxembourg’s financial center and is recognized for its strong academic and industry links. It includes more than 15 research-oriented faculty members with backgrounds from institutions such as:

• New York University

• University of Lausanne

• University of Rochester

• Carnegie Mellon University

The department is also closely connected with major financial and policy institutions, including:

• Luxembourg Financial Centre

• European Stability Mechanism

• Central Bank of Luxembourg

This creates a highly international and research-driven academic environment.

Research Areas

Applicants will work in areas such as:

• Finance

• Economics

• Statistics and Econometrics

• Quantitative Finance

• Computational Economics

Eligibility Criteria

Applicants should meet the following requirements:

• Strong interest in Finance, Economics, or Econometrics

• Background in a quantitative field such as:

  • Mathematics

  • Physics

  • Computer Science

  • Engineering

• Strong analytical and computational skills

• Minimum B2 level English proficiency

• Relevant academic degree (Master’s or equivalent for PhD entry)

Scholarship and Funding

The PhD position includes full financial support:

• Competitive annual salary (€41,976 gross)

• Full-time employment contract (36 months)

• Financial support during the MQEF first-year coursework

• Access to university research facilities and international academic network

Required Application Documents

Applicants must submit:

• Curriculum Vitae (CV)

• Motivation letter

• Academic transcripts (all university-level results)

• Degree certificates

• Proof of English proficiency (if required)

Reference letters may also be requested depending on the selection stage.

How to Apply

To apply for the University of Luxembourg PhD in Finance:

1. Submit your application through the official online HR system

2. Include all required documents in your application

3. Also apply through the MQEF program portal (mandatory)

4. Applications sent by email are not accepted

Applications are reviewed on a rolling basis, so early submission is strongly recommended.

Contract Details

• Position Title: Doctoral Researcher

• Contract Type: Fixed-term (36 months)

• Working Hours: Full-time (40 hours/week)

• Location: Belval Campus, Luxembourg

Why Choose the University of Luxembourg?

The University of Luxembourg offers:

• A multilingual and international academic environment

• Strong ties with European institutions and the financial sector

• Collaboration with global universities and research centers

• High-quality infrastructure and research facilities

• A diverse academic community from over 90 countries

Overview of the Opportunity

Nottingham Trent University is offering a fully funded PhD studentship focused on an AI-aided, data-driven approach to studying historical parchments. The project investigates the making, degradation, and origin of ancient parchment materials using advanced computational and scientific methods.

About Nottingham Trent University

Nottingham Trent University is a well-established public research university in the United Kingdom known for its strong focus on applied research, innovation, and interdisciplinary studies. It actively promotes inclusive research environments and collaboration across international institutions.

Research Focus

This PhD project combines artificial intelligence, data science, and heritage science to explore:

• Manufacturing processes of historical parchments

• Degradation mechanisms over time

• Origins and material composition of manuscripts

• Applications of AI in conservation science

• Archaeological and cultural heritage analysis

The research contributes to both digital innovation and historical preservation.

Supervisory Team

Supervisor: Jens Binder
Institution: Nottingham Trent University

Funding and Financial Support

This PhD studentship is jointly funded by:

• Nottingham Trent University (UK)

• University of Namur (Belgium)

Funding includes:

• Full tuition fee coverage

• Annual stipend for living expenses

Eligibility Criteria

Applicants must meet the following requirements:

• Background in physical sciences, bioinformatics, or related fields

• Interest in heritage science, conservation science, or archaeological science

• Strong motivation for interdisciplinary research

• Ability to work in a data-driven and computational research environment

Application Deadline

Deadline: June 15, 2026

How to Apply

Step 1: Review Requirements

Check eligibility and application guidance on the university’s official PhD application page.

Step 2: Prepare Application Documents

Applicants typically need:

• Academic CV

• Motivation letter

• Academic transcripts

• Relevant research experience details

Step 3: Submit Application

Applications must be submitted through the official Nottingham Trent University application system.

Step 4: Selection Process

Shortlisted candidates may be contacted for interviews and further assessment.

Important Notes

• The program encourages applications from underrepresented groups

• Strong interdisciplinary and analytical skills are highly valued

• The project involves collaboration between UK and Belgian institutions

Conclusion

The AI-aided PhD studentship at Nottingham Trent University 2026 is a unique opportunity for students interested in combining artificial intelligence with heritage science. With full funding and international collaboration, it offers a strong platform for research in cultural preservation and data-driven scientific analysis.

For official application details, candidates should visit the Nottingham Trent University PhD admissions page.

Overview of the Opportunity

The Technical University of Munich (TUM) is offering two fully funded PhD positions in Electronic Structure Theory and Quantum Transport under the supervision of Prof. Dr. Frank Ortmann. These positions focus on advanced computational physics and materials science research, with the opportunity to earn a doctoral degree at one of Europe’s top-ranked universities.

About Technical University of Munich

The Technical University of Munich is one of Europe’s leading research universities, known for excellence in engineering, physics, and technology. It is closely connected with major research initiatives such as the Munich Center for Quantum Science and Technology and provides a highly international research environment.

Research Group and Supervision

These PhD positions are offered in the research group of Prof. Dr. Frank Ortmann at TUM. The group focuses on developing advanced theoretical and computational models to study electronic, optical, and transport properties of complex materials.

Research Topics

Project A: Electronic Structure and Optical Excitations

• Development of linear-scaling Wannier optics methods

• Simulation of optical excitations in large material systems

• Study of excitonic effects and many-body interactions

• Quantum dynamics in complex materials

Project B: Quantum Transport in Polymers

• Modeling electron-phonon coupling

• Development of efficient quantum transport frameworks

• Application to polymer-based materials

Program Duration and Start Date

Duration: 3 years
Start Date: Summer 2026 (flexible)

Salary and Funding

• Employment based on German public sector TV-L E13 scale

• Fully funded research associate position

• Access to TUM Graduate School and international research networks

• Conference participation support

Eligibility Criteria

Applicants must meet the following requirements:

• Master’s degree in Physics, Chemistry, or related field

• Strong background in theoretical solid-state physics or theoretical chemistry

• Interest in electronic structure theory and computational modeling

• Programming or simulation experience is an advantage

• Excellent English communication and writing skills

Required Documents

Applicants must submit:

• Curriculum Vitae (CV)

• Motivation letter

• Academic transcripts

• Degree certificates

• Optional: up to two reference letters

Application Deadline

Deadline: April 21, 2026

How to Apply

Step 1: Prepare Application

Combine all required documents into a single PDF file.

Step 2: Send Application Email

Submit your application to the official email provided by the research group.

Step 3: Email Subject Line

Use the correct subject format:

• Application PhD2026-2a (for Project A)

• Application PhD2026-2b (for Project B)

Step 4: Recommendation Letters

Reference letters can be sent separately by referees directly to the same email address.

Step 5: Selection Process

Candidates are selected based on academic background, research potential, and motivation.

Key Notes

• Candidates are encouraged to specify their preferred research project

• Strong independent and collaborative research skills are required

• International applicants are welcome

• Women and candidates with disabilities are encouraged to apply

Conclusion

The PhD positions at the Technical University of Munich 2026 provide an excellent opportunity to pursue advanced research in quantum physics and computational materials science. With full funding, strong academic supervision, and access to world-class facilities, this program is ideal for students aiming to build a research career in theoretical physics.

For official details and application submission, applicants should contact the research group at TUM directly.