PhD Position at the SDU Centre for Software Technology

The Centre for Software Technology (CST) part of Maersk McKinney Moller Institute in the Faculty of Engineering at the University of Southern Denmark (SDU) invites applications for a 3-year PhD position. The position is open fromMay1 2026 or as soon as possible thereafter and the specific start date will be agreed with the successful candidate.

What we offer:

The Centre values teamwork professional diligence enthusiasm for technology and the drive to adopt new skills and extended responsibilities. We offer an open international team with flexible work organization and support of individual development. The group is involved in a variety of national and European projects and features a strong network of academic and industrial partners. We solve challenging research problems from real applications and implement novel software and solutions together with end users.

We are looking for a candidate for the following PhD project:

PhD Position in Sustainable AI for the Environment Promoting a Green Transition

What we expect:

The applicant should have completed a Masters degree (MS / MSc / MTech / ME etc.) in Software Engineering Information Technology Computer Science Artificial Intelligence Data Science Robotics or any other relevant field prior to receiving admission into this PhD program i.e. we accept applications from candidates expecting to finalize their studies within the upcoming months.

Please scroll down to read more about the expectations in terms of PhD candidate responsibilities qualifications required skills (mandatory) and additional skills (preferred) with respect to the PhD position.

Workplace description:

The Centre for Software Technology (CST) at SDU is a part of the new campus SDU Vejle home of excellence within information technology. The academic focus of the SDU Centre for Software Technology is to conduct research in interactive information technology and software engineering. The areas will be complementing each other to make way for the engineering of the next generation of reliable intelligent and interactive software solutions. This includes understanding how AI technologies and data-informed software development with a human-centred perspective can change the engineering of products and software infrastructures.

Further Information:Please visit our website for more details; and feel free to reach out to the contact persons by email in case you have any more questions.

Project Description - PhD Position in Sustainable AI for the Environment Promoting a Green Transition

In recent years there is a need for studying and using sustainable AI methods to head towards a green transition. This is particularly important for environmental initiatives to achieve the targeted 2050 climate neutral goals of the EU as well as the United Nations Sustainable Development Goals (UN SDGs). These initiatives are in line with Denmarks ambitious 2045 climate neutrality target as well. Promising research directions in the initiatives include investigating sustainable machine learning approaches and addressing renewable energy related projects. Likewise deploying a novel paradigm of KGML (knowledge guided machine learning) can propel further research.

PhD candidate responsibilities:

The PhD candidate will be responsible for conducting research and implementation in areas such as:

• Exploring KGML in environmental science e.g. in renewable energy related projects; this can entail working alongside domain experts to extract relevant knowledge and programming using suitable models to infuse that knowledge with ML methods thus aiming to optimize performance and interpretability analogous to RAG (Retrieval-Augmented Generation) in LLMs
• Investigating methods for improving AI model sustainability e.g. model compression techniques (such as quantization and pruning) carbon-aware computing minimizing algorithmic complexity maintenance requirements mapping energy efficiency and related aspects using KPI (key performance indicators) with respect to ESG (environmental social governance) parameters.
• Developing tools and prototypes (programs mobile apps or web interfaces) to validate and dissiminate research findings (e.g. systems for environmental decision support urban planning energy optimization etc.). Designing knowledge bases for further use in KGML; and investigating the use of KGML and Interpretable AI to explain complex green transition concepts to users (e.g. via intelligent tutoring system (ITS) or interactive interfaces).

Qualifications for application:

The candidate should complete a Masters degree (MS / MSc / MTech / ME etc.) in Computer Science or Information Technology or Software Engineering or Artificial Intelligence or Data Science or Environmental Science or any other relevant field prior to admission into this PhD program.

Required skills (mandatory):

• Strong understanding of sustainable AI or related areas
• Experience of programming in Python / C / Java or equivalent
• Experience with using Machine Learning software e.g. PyTorch / TensorFlow / Scikit Learn
• Highly knowledgeable in mathematical and statistical concepts
• Solid foundation in mathematics for Machine Learning (Linear Algebra Probability Optimization).
• Proficient in English for technical writing oral presentations and general communication

Additional experience (preferred):

• Familiarity with the KGML paradigm and its implementation
• Working with domain experts in Environmental Science & Engineering
• Expertise in model compression techniques like quantization and pruning
• Successful development of apps and websites with real-world deployment

Contact persons:

Dr. Aparna Varde Full Professor Centre for Software Technology (CST) SDU Vejle (E-mail: )

Dr. Emil Njor Assistant Professor Centre for Software Technology SDU Vejle (E-mail: )

Dr. Mikkel Baun Kjaergaard Full Professor LEGO Chair Head of Education SDU Vejle (E-mail: )

Dr. Torben Worm Head of Section Software Engineering and CST at SDU (E-mail: )

Application Due Date: April 7 2026 at 11:59 PM / 23:59 (CET/CEST)

Application Procedure:

Before applying the candidates are advised to read theFaculty information for prospective PhD studentsand theSDU information on how to apply.

Assessment of the candidates is based on the application material and an application must include:

• Motivated application.
• Curriculum Vitae.
• Masters and bachelors degree certificates or equivalent including transcripts of grades (original and an official English translation).
• Completed TEK PhD application form for 5-3 applicants. Find the form at the Faculty website.
• Completed TEK PhD form for calculation grade point average. Find the form at the Faculty website.
• An official document describing the grading scheme of the awarding universities (if not Danish).
• Only for applicants from programmes that evaluate thesis/examination project by approved/not approved:An official written assessment of the thesis or dissertation project from the grade giving institution. The statement must clearly state that the candidate has been among the top 30 the graduation class for the study programme.
• List of publications and maximum 2 examples of relevant publications (in case you have any publications).
• References may be included youre welcome to use the form for reference letter at the Faculty website.
• A statement/documentation of other qualifications relevant to the position may also be included.

All documents must be in English and PDF format. CPR number (civil registration number) must be crossed out. All PDF-files must be unlocked allow binding and may not be password protected.

SUBMISSION GUIDE: Motivated application must be uploaded under Cover letter (max. 5 MB) Curriculum Vitae must be uploaded under Resume (max 5 MB). All other documents must be uploaded under Miscellaneous documents (max 10 files with a maximum 50 MB per file).

Assessment and selection process:

Applications will be assessed by an assessment committee. Shortlisting may be applied and only shortlisted candidates will receive a written assessment.Read about shortlisting at and tests may be part of the overall about theAssessment and selection process.

Conditions of enrollment/employment:

Appointment as a PhD fellow is a 3-year salaried position and the monthly gross salary (including pension) is competitive.

The position is available May 1 2026 (or as soon as possible thereafter negotiated with the selected PhD candidate)

Applicants must hold a masters degree (equivalent to a Danish masters degree) at the time of enrollment and employment. Employment is contingent on enrollment approved by the PhD School. Enrollment will be in accordance with Faculty regulations and the Danish Ministerial Order on the PhD Programme at the Universities (PhD order). Employment will be in accordance with the collective agreement between the Ministry of Finance and the Danish Confederation of Professional Associations for academics in the state with the associated circular on the job structure for academic staff at Danish universities and the provisions for PhD fellows as described herein as well as the Protocol on PhD fellows signed by the Danish Ministry of Finance and the Danish Confederation of Professional Associations (AC). The person employed in the position may based on a specific individual managerial evaluation be exempted from time registration also known as a self-organizer.

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The University of Southern Denmark wishes its staff to reflect the surrounding community and therefore encourages everyone regardless of personal background to apply for the position. SDU conducts research in critical technologies which due to the risk of unwanted knowledge transfer is subject to a number of security measures. Therefore based on information from open sources background checks may be conducted on candidates for the position(s).

Further informationfor international applicants about entering and working in Denmark. You may also visitWorkinDenmarkfor additional information.

Further informationabout The Faculty of Engineering.