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 from May 1, 2026, 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 PhD candidate for the following PhD project:

PhD Position in Explainable AI with Commonsense Knowledge

(Please scroll down to read more about the project description.)

What we expect

The applicant should have completed a Master’s degree (MS / MSc / MTech / ME etc.) in Software Engineering, Information Technology, Computer Science, Artificial Intelligence, Data Science, Robotics or any other relevant field, at the time of admission into this PhD program. Students currently enrolled in Master’s programs can apply, provided they will receive their Master’s degree prior to joining this PhD position at SDU. 

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 each 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 Explainable AI with Commonsense Knowledge

In this project, we aim to investigate the paradigm of explainable AI (i.e. XAI), especially with reference to its interesting facet of commonsense knowledge (CSK). 

As an application area to highlight the importance of this paradigm in the realm of intelligent systems, we consider an example domain of domestic and service robots. These robots are increasingly being deployed in environments designed for people. Beyond just avoiding physical obstacles, these robots must understand the social physics of human interaction, such as recognizing that standing too close to a person or interrupting a conversation is inappropriate behavior. 

By leveraging XAI with CSK, the robot can interpret the context of a room, recognizing that a person holding a tray needs the right-of-way or that a closed door might imply a private meeting. XAI methods allow robots to articulate these complex social decisions to the humans nearby, providing verbal or visual justifications for its movements that foster a sense of safety and predictability in domestic or office settings. 

Note that there is growing trend towards XAI today. Opaque-box models with deep learning (DL) might potentially offer high accuracy but are not explainable due to which there can be problems in interpretation, trust, error tracing etc. On the other hand, XAI methods offer clear-box models, often comparable to DL in accuracy, yet better in 1st-time scenarios (where the AI has not exactly encountered the given situation with pre-training earlier), as well as in counterbalancing bias & overfitting. 

In addition to classical XAI models, e.g. decision trees, there is the paradigm of commonsense knowledge (CSK), i.e. everyday knowledge on concepts, properties, and relationships. It is easy for humans and often the hardest for AI systems (vs. encyclopedic knowledge). It often involves design of KBs (knowledge bases) with CSK followed by extraction and use in targeted applications. 

This project entails involvement of CSK and other XAI methods in intelligent systems, considering the given application domain.  

PhD candidate responsibilities

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

• Exploring trust in conjunction with XAI, along with human-AI interaction and collaboration, since humans and AI systems can obviously trust each other better if tasks are more interpretable

• Considering subjective issues on the needs of humans working with robots from a CSK (commonsense knowledge) perspective, e.g. boredom, encumbrance, comfort, and pleasure

• Defining specific CSK-premises (in addition to CSK from existing KBs) in the targeted application avenues along with mathematical modeling and algorithmic insights

• Counterbalancing issues such as bias, overfitting, and inexplicable errors in excessive pre-training: by making systems explicitly aware of the reasons behind their actions using XAI

• Performing experiments on XAI with CSK in real-world environments, e.g. with a turtle robot, in specific contexts such as grocery stores, restaurants, and households. 

Qualifications for application 

The candidate should have a Master’s degree (MS / MSc / MTech / ME etc.) in Computer Science or Information Technology or Software Engineering or Artificial Intelligence or Data Science or Robotics or any other relevant field, at the time of application into this PhD program. 

Required skills (mandatory)

• Well-versed with a general background of Artificial Intelligence (AI) along with Robotics

• Excellent programmer in Java / C / Python  / ROS or equivalent

• Excellent at using Machine Learning software, e.g. PyTorch / TensorFlow / Scikit Learn  

• Highly knowledgeable in mathematical and statistical concepts

• Proficient in English for technical writing, oral presentations, and general communication

Additional experience (preferred)

• Very good knowledge of XAI techniques 

• Thorough understanding of KB development

• Working with specific applications in robotics and intelligent systems

Contact 

Dr. Aparna Varde, Full Professor, Centre for Software Technology, SDU Vejle (email: apva@mmmi.sdu.dk) 

Dr. Juan Esteban Heredia Mena, Assistant Professor, Software Engineering, SDU (email: jehm@mmmi.sdu.dk) 

Dr. Mikkel Baun Kjaergaard, LEGO Chair, Full Professor, Head of Education, SDU Vejle (email: mbkj@mmmi.sdu.dk) 

Dr. Torben Worm, Head of Section, Software Engineering, CIS, and CST, at SDU (email: tow@mmmi.sdu.dk) 

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

Application

Before applying the candidates are advised to read the Faculty information for prospective PhD students and the SDU information on how to apply.

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

• Motivated application. 

• Curriculum Vitae.

• Master’s and Bachelor’s 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 pct. in 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, you're 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). 

If you experience technical problems, please contact our email support.

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 SDU.  Interviews and tests may be part of the overall evaluation. Read about the Assessment and selection process.  

Conditions of enrollment/employment

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

The position is available May 1, 2026, or as soon as possible thereafter; it will be agreed with the successful candidate.

Applicants must hold a master’s degree (equivalent to a Danish master's 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 including the associated circular on the job structure for academic staff at Danish universities and the provisions for PhD fellows as described therein as well as the Protocol on PhD fellows signed by the Danish Ministry of Finance and the Danish Confederation of Professional Associations (AC). Further information about salary and conditions of employment. Persons employed in the position may, based on a specific individual managerial assessment, 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 information for international applicants about entering and working in Denmark. You may also visit WorkinDenmark for additional information.

Further information about The Faculty of Engineering.