PhD in Airline Operations and Sustainable Aviation Networks

Mixed Fleets of Novel Aircraft – Network Development and Scheduling
Delft University of Technology
Delft, Netherlands
Application Deadline: 16 March 2026

Fully Funded PhD in Sustainable Airline Operations

The Delft University of Technology (TU Delft) is offering a fully funded PhD position within the Faculty of Aerospace Engineering. This doctoral project focuses on airline operations, fleet planning, and sustainable aviation systems, addressing one of the most critical questions in aviation:

How can airlines integrate sustainable aircraft technologies into future networks while maintaining economic viability?

This research lies at the intersection of aerospace engineering, operations research, transportation systems, and climate-focused aviation innovation.

Research Focus: Airline Decision Models for Novel Aircraft Technologies

Global air traffic demand continues to grow, while aviation must significantly reduce its climate impact. New aircraft concepts powered by hydrogen and battery-electric propulsion systems introduce new operational constraints and opportunities, including changes in:

• Aircraft range and payload

• Charging and refueling infrastructure

• Airport compatibility

• Flight performance characteristics

• Scheduling and frequency planning

This PhD project develops advanced mathematical models and computational tools to support:

• Strategic airline network development

• Mixed fleet composition decisions

• Aircraft introduction timing

• Sustainable scheduling optimization

• Tactical operational planning

The goal is to help airlines, aircraft manufacturers, and policymakers make data-driven decisions about integrating next-generation aircraft into commercial networks.

Academic Field and Research Domain

This PhD lies within the following disciplines:

Primary Field

• Aerospace Engineering

Core Research Areas

• Airline Operations Research

• Transportation Systems Engineering

• Network Optimization

• Sustainable Aviation Systems

• Mathematical Modelling and Optimization

Application Domain

• Hydrogen-powered aircraft

• Battery-electric aircraft

• Climate-neutral aviation

• Aviation energy transition

The project contributes directly to the broader themes of sustainable aerospace and decarbonization of air transport.

Research Responsibilities

As a PhD candidate, you will:

• Develop mathematical models for long-term airline planning

• Create optimization algorithms for mixed fleet scheduling

• Build computational tools for strategic network analysis

• Integrate operational, tactical, and environmental considerations

• Collaborate with aircraft designers and performance experts

• Contribute to the Dutch DASAL research project

• Publish in leading aerospace and transportation journals

• Present findings at international conferences

• Supervise laboratory sessions and mentor master’s students

You will work within the Operations and Environment section, an interdisciplinary research group focused on sustainable and adaptive air transport systems.

Required Qualifications

Applicants should have:

• An MSc in Aerospace Engineering, Mechanical Engineering, Operations Research, Transportation Engineering, or a related field

• Strong analytical and modelling skills

• Experience with mathematical optimization

• Advanced Python programming skills

• Proficiency in written and spoken English

Knowledge of aircraft technology and flight performance modelling is considered an advantage.

Employment Conditions and Benefits

PhD candidates at Delft University of Technology are appointed for four years, structured as:

• Initial 1.5-year contract with performance assessment

• Followed by a 2.5-year extension upon positive evaluation

Salary

• €3,059 to €3,881 gross per month (based on full-time employment)

• 8% holiday allowance

• 8.3% end-of-year bonus

Additional benefits include:

• Enrollment in the TU Delft Graduate School

• Structured Doctoral Education Programme

• Flexible working arrangements

• Relocation support services

• Dual Career Programme for partners

• Inclusive and diverse academic environment

Research Environment: Faculty of Aerospace Engineering

The Faculty of Aerospace Engineering at Delft University of Technology is internationally recognized for research in:

• Energy transition in aviation

• Sustainable aerospace technologies

• Aviation safety and security

• Climate-resilient mobility systems

The faculty collaborates with research institutes, industry, and government stakeholders across Europe to advance sustainable aviation solutions.

Application Requirements

Applicants must submit:

• Detailed CV

• Motivation letter

• BSc and MSc diplomas and transcripts

Candidates must demonstrate English proficiency suitable for doctoral education and academic publication.

Applications must be submitted through the official TU Delft application system before the deadline.

Career Opportunities

Graduates of this PhD will develop expertise in:

• Sustainable aviation systems

• Airline network optimization

• Mixed fleet modelling

• Aviation decarbonization strategy

• Computational modelling for transportation systems

Career pathways include academia, aviation consulting, aircraft manufacturing, airline strategy departments, transportation policy, and sustainability advisory roles.

Study and Live in Delft, Netherlands

Delft is a leading European innovation hub, known for its strong engineering tradition and international research community. As a PhD candidate, you will join a collaborative academic environment committed to technological solutions for global climate challenges.

This PhD in Airline Operations for Mixed Fleets of Novel Aircraft is ideal for candidates passionate about aerospace engineering, sustainability, optimization modelling, and shaping the future of climate-neutral aviation.

Apply now at : https://careers.tudelft.nl/job/Delft-PhD-Airline-Operations-for-Mixed-Fleets-of-Novel-Aircraft-From-Network-Development-to-Scheduling-2628-CD/1353373557/

If you are planning to pursue a PhD in Europe at the intersection of artificial intelligence and healthcare, the opportunity at Linköping University is a strong choice. This fully funded PhD focuses on deep learning for medical imaging, with real-world applications in early lung cancer detection.

PhD Position Overview

• University: Linköping University

• Location: Linköping

• Department: Biomedical Engineering

• Supervisor: Anders Eklund

• Program: Data-Driven Life Science (DDLS)

• Degree Level: PhD

• Duration: 4–5 Years

• Deadline: May 14, 2026

Research Focus

This PhD is part of Sweden’s national Data-Driven Life Science (DDLS) initiative, aimed at advancing AI-driven biomedical research.

The project focuses on:

• Deep learning for medical image analysis

• Early detection of lung cancer

• Combining:

  • High-resolution CT scan data

  • Clinical variables (age, smoking status, etc.)

• Classifying lung nodules as benign or malignant

The research uses large-scale datasets (30,000+ subjects) and aims to improve diagnostic accuracy in healthcare systems.

Key Research Areas

• Computer vision for medical imaging

• Deep learning model development

• Multi-modal data fusion (imaging + clinical data)

• Large-scale biomedical data analysis

• AI applications in precision medicine and diagnostics

Scholarship Benefits

The PhD position offers:

• Starting salary of SEK 36,400/month (increases annually)

• Fully funded PhD training (no tuition fees)

• Access to advanced AI infrastructure, including:

  • High-performance computing systems

• Participation in a national research program (DDLS)

• Collaboration with:

  • Hospitals

  • AI research labs

• Opportunities for teaching (up to 20%)

Eligibility Criteria

Applicants must meet the following requirements:

• Master’s degree in:

  • Biomedical Engineering

  • Computer Science

  • Machine Learning

  • Electrical Engineering

  • Statistics or related fields

• Strong background in:

  • Deep learning

  • Computer vision

  • Mathematics

• Programming skills (especially Python)

• English language proficiency

Preferred qualifications:

• Experience in medical image analysis

• Knowledge of large-scale data processing

Responsibilities

Selected candidates will:

• Develop AI models for lung cancer detection

• Analyze large medical imaging datasets

• Collaborate with clinicians and researchers

• Publish research in scientific journals

• Participate in academic discussions and research meetings

Research Environment

Linköping University is one of Sweden’s leading institutions in AI and engineering, with strong links to national initiatives such as:

• DDLS (Data-Driven Life Science)

• WASP (AI research program)

• ELLIIT (IT and mobile communication research)

The research group collaborates closely with hospitals and international partners, providing a highly interdisciplinary environment.

Application Process

To apply, candidates must:

• Submit an online application before the deadline

• Include academic transcripts and CV

• Provide proof of qualifications and experience

Late or incomplete applications will not be considered.

Why Study in Sweden?

Sweden offers:

• High-quality research and education

• Strong focus on innovation and AI

• Excellent work-life balance

• International and inclusive academic culture

Final Thoughts

This PhD in Biomedical Engineering is ideal for candidates interested in AI, healthcare, and real-world impact. With access to large datasets, advanced computing resources, and interdisciplinary collaboration, it provides an excellent platform for building a career in medical AI research.

If you are planning to pursue a fully funded PhD in sustainable energy, the opportunity at University of Stavanger offers an excellent pathway into advanced research in geothermal systems. This PhD fellowship focuses on optimizing energy transfer in shallow geothermal wells, combining experimental work, modeling, and AI-driven optimization.

PhD Position Overview

• University: University of Stavanger

• Location: Stavanger

• Department: Energy and Petroleum Engineering

• Supervisor: Kristian Gjerstad

• Degree Level: PhD

• Start Date: August 2026

• Duration: 3 Years

• Deadline: May 30, 2026

Research Focus

This PhD project explores efficient and sustainable geothermal energy systems, aiming to improve heating and cooling technologies.

Key research objectives include:

• Optimizing energy transfer in shallow geothermal wells

• Reducing energy losses in circulation systems

• Improving cost efficiency per kWh

• Developing thermal and hydraulic models

• Applying AI-based and hybrid optimization methods

Key Research Questions

• How does well design affect heat transfer and energy losses?

• What operating conditions maximize energy output?

• How can models better predict geothermal system performance?

Research Tasks

The selected candidate will work on:

• Experimental studies on heat transfer and pressure loss

• Building and modifying flow loop systems

• Developing computational thermal and hydraulic models

• Applying AI and control algorithms for system optimization

• Validating models using real-world data

Expected Outcomes

The project aims to deliver:

• Advanced models for geothermal system design

• Improved energy efficiency and sustainability

• Practical solutions for future green energy systems

Scholarship Benefits

This fully funded PhD includes:

• Annual salary of NOK 550,800

• Pension and insurance benefits

• Access to Norway’s public healthcare system

• Paid parental leave and social benefits

• Free Norwegian language courses

• Relocation support

• Access to sports facilities and wellness services

Eligibility Criteria

Applicants must meet the following requirements:

• Master’s degree in:

  • Energy Engineering

  • Physics

  • Computer Science

  • Petroleum Engineering or related fields

• Strong academic record (minimum grade equivalent to B)

• Skills in:

  • Numerical modeling

  • Data analysis or AI

• Experience in:

  • Experimental work (preferred)

  • Software development

• Strong English proficiency

English Language Requirements

Applicants must provide one of the following:

• TOEFL (minimum 90)

• IELTS (minimum 6.5)

• Cambridge CAE/CPE

• PTE Academic (minimum 62)

Exemptions apply for candidates with prior education in English-speaking countries or EU/EEA programs.

Application Requirements

To apply, candidates must submit:

• CV and academic records

• Motivation letter

• Research proposal (mandatory)

• Certificates and diplomas

• Proof of English proficiency

• Relevant publications (if available)

Applications must be submitted through the official online portal.

Why Choose Stavanger?

Stavanger is a leading energy hub in Europe, making it an ideal location for research in sustainable technologies. The University of Stavanger is known for:

• Strong industry collaboration in energy sectors

• Focus on green transition and sustainability

• International research environment

• High quality of life and work-life balance

Final Thoughts

This PhD fellowship is ideal for candidates interested in renewable energy, AI-driven optimization, and engineering innovation. With strong financial support and access to cutting-edge research facilities, it offers a valuable opportunity to contribute to the future of sustainable energy systems.

If you are planning to pursue a PhD in Europe with strong financial support, the opportunity at Eindhoven University of Technology is one of the best options available. This fully funded PhD position in Statistical Bioinformatics offers competitive salary, advanced research training, and access to a world-class innovation ecosystem in the Netherlands.

Overview of the PhD Position

• Host Institution: Eindhoven University of Technology

• Location: Eindhoven

• Department: Mathematics and Computer Science

• Supervisor: Jeanine Duistermaat

• Degree Level: PhD

• Deadline: May 16, 2026

• Duration: 4 Years

• Employment Type: Full-time

Research Focus

This PhD project focuses on statistical data integration in biomedical research, particularly using advanced models for complex biological datasets.

Key research areas include:

• Development of latent variable models for multi-omics data

• Statistical modeling of longitudinal biological datasets

• Integration of datasets such as:

  • Proteomics

  • Metabolomics

  • Transcriptomics

• Assessing model performance and goodness-of-fit

• Creating R packages for practical implementation

The research contributes directly to improving understanding of disease mechanisms, diagnosis, and treatment strategies.

Scholarship Benefits

The PhD position offers a strong financial and professional package:

• Monthly salary between €3,059 – €3,881

• Annual bonuses:

  • 8.3% year-end bonus

  • 8% holiday allowance

• Pension scheme and paid leave benefits

• Travel, remote work, and internet allowances

• Access to:

  • High-quality research infrastructure

  • Training and career development programs

  • Sports and campus facilities

• Support for international candidates, including relocation assistance

Eligibility Criteria

To qualify for this PhD position, applicants must meet the following requirements:

• Master’s degree in:

  • Mathematics

  • Statistics

  • Or a closely related field

• Strong background in:

  • Statistical modeling

  • Data analysis

• Interest in biomedical applications and interdisciplinary research

• Good communication and academic writing skills

• English proficiency (minimum C1 level)

Additional advantages:

• Experience with biological datasets

• Programming skills (especially in R or similar tools)

Responsibilities

Selected candidates will:

• Develop new statistical methods for multi-omics data

• Apply models to real-world biomedical datasets

• Build and maintain software tools (R packages)

• Collaborate with interdisciplinary research teams

• Present research at conferences and publish findings

• Contribute to teaching (10–15% workload)

Application Process

To apply, candidates must submit:

• Motivation letter

• Updated CV (including publications and references)

• Academic transcripts

• Contact details of referees

Applications must be submitted through the official online portal. Incomplete or email submissions are not accepted.

Why Choose TU Eindhoven?

Eindhoven University of Technology is located in the Brainport Eindhoven region, one of Europe’s leading technology hubs. The university is known for:

• Strong collaboration with high-tech industries

• Cutting-edge research in AI, data science, and engineering

• A highly international academic environment

• Practical, impact-driven research approach

Final Thoughts

This PhD in Statistical Bioinformatics is ideal for candidates who want to combine advanced mathematics, data science, and biomedical research in a fully funded European program. With strong academic support and industry connections, it offers an excellent pathway for a research career in data-driven healthcare.

The University of Luxembourg is offering a fully funded PhD position in Civil Engineering with a focus on hybrid composite structures. This doctoral opportunity is part of the European HySCom project, aimed at developing next-generation structural systems using advanced materials such as UHPC and steel-concrete composites.

The position is hosted by the Faculty of Science, Technology and Medicine (FSTM) and provides a strong combination of experimental research, numerical modelling, and industry collaboration.

PhD Position Overview

• Level of Study: PhD (Doctoral Researcher)

• Institution: University of Luxembourg

• Faculty: Faculty of Science, Technology and Medicine (FSTM)

• Department: Engineering (DoE)

• Supervisor: Markus Schäfer

• Location: Luxembourg City (Kirchberg Campus)

• Duration: 36 months

• Start Date: June 15, 2026

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

• Language Requirement: English (minimum B2 level)

Project Overview – HySCom

This PhD position is part of the Eurostars HySCom project, focusing on the development of innovative hybrid composite columns combining:

• Reinforced concrete

• Structural steel

• Steel Fibre Reinforced Ultra-High Performance Concrete (SFRUHPC)

The project is conducted in collaboration with a leading German industrial partner, providing real-world engineering applications alongside academic research.

Research Areas

The doctoral research will include:

• Material characterization of concrete and UHPC

• Development and optimization of UHPC mixtures

• Experimental testing (small-scale and large-scale structural tests)

• Push tests and column tests

• Advanced nonlinear finite element modelling (Abaqus)

• Fire and ambient condition simulations

• Structural design model development

• Parametric studies and model validation

Key Responsibilities

The selected candidate will:

• Conduct laboratory-based experimental research

• Develop and validate computational models

• Perform 3D nonlinear FEM simulations

• Publish results in international journals

• Present findings at global conferences

• Support teaching and academic activities

Eligibility Criteria

Applicants must meet the following requirements:

Education

• Master’s degree in:

  • Civil Engineering

  • Structural Engineering

  • Related engineering discipline

Technical Skills

• Strong knowledge of:

  • Structural engineering

  • Steel–concrete composite systems

  • Construction materials (concrete, UHPC)

• Familiarity with:

  • Eurocodes (EN 1990, EN 1992, EN 1993, EN 1994)

• Experience with:

  • Nonlinear FEM (preferably Abaqus, GMNIA)

Additional Requirements

• Interest in experimental and numerical research

• Strong analytical and problem-solving skills

• English proficiency (minimum B2 level)

Salary and Benefits

This is a fully funded doctoral position offering:

• €41,976 annual gross salary

• Full-time employment (40 hours/week)

• Access to advanced laboratory and simulation facilities

• Collaboration with industry partners

• Opportunities to attend international conferences

• Multicultural research environment

Required Application Documents

Applicants must submit:

• Curriculum Vitae (CV)

• Motivation letter

• Academic transcripts

• Contact details of 1–2 referees

Applications must be submitted through the official online system. Email applications are not accepted.

How to Apply

To apply for this PhD position:

1. Prepare all required documents

2. Submit your application through the official University of Luxembourg HR portal

3. Apply as early as possible (rolling selection process)

Contract Details

• Position Title: Doctoral Researcher

• Contract Type: Fixed-term (36 months)

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

• Campus: Kirchberg, Luxembourg

About the Faculty (FSTM)

The Faculty of Science, Technology and Medicine at the University of Luxembourg is a multidisciplinary hub covering:

• Engineering

• Computer Science

• Physics and Mathematics

• Life Sciences and Medicine

The Department of Engineering focuses on innovative and sustainable solutions for modern infrastructure and industry challenges.

Why Apply for This PhD?

This opportunity is ideal for candidates who want to:

• Work on cutting-edge composite materials and structures

• Gain hands-on laboratory and simulation experience

• Collaborate with industry partners

• Build an international research career in Europe

• Contribute to sustainable infrastructure development