Doctoral student in Computer Science with focus on AI engineering Full-time NEW

Doctoral Student In Computer Science With Focus On Ai Engineering

The doctoral student will be employed at the Department of Computer Science, where research on engineering of large-scale software-intensive systems is conducted in the Software Engineering unit. The unit is a world leader on empirical software engineering. In addition to conventional software, the scope includes engineering of AI enabled systems (primarily ML and LLM), and thus MLOps (Machine Learning Operations), datacentric AI, and legal and ethical aspects of AI.

The empirical research catalyzes industry-academia collaboration and cross-disciplinary initiatives, in which the doctoral student may conduct their studies. Particularly, this position is funded within the ELLIIT strategic research area (Excellence Center at Linköping – Lund in Information Technology) where a twin doctoral student will address the same topic from a business perspective. The student will also be affiliated with the NextG2Com industrial competence center, in the research theme on Integrated Data Engineering and Machine Learning.

As a doctoral student, you are both admitted as a student and employed at Lund University. As a doctoral student, you will be trained in a scientific approach. In short, you will be trained to think critically and analytically, to solve problems independently using the right methods, and to develop an awareness of research ethics. In addition, you will have the opportunity to work on projects, to develop your leadership and pedagogical skills. Throughout your studies, you will be guided by supervisors. Doctoral studies end with a thesis and a doctoral degree.

The study subject is computer science with a focus on AI engineering, i.e. engineering of systems containing AI-based features (LLM or ML). Application domains range from agentic software engineering to industrial control systems. Specifically, it addresses the issue of using general vs. specialized models (e.g. per task, company, country or domain). From a technical perspective, there are a multitude of factors to trade across the range of generalization–specialization, including model performance, energy consumption, training data supply, and integrity of data. The project aims to address AI engineering in business-to-business (B2B) contexts in various industry domains, as well as open source AI models. We perform empirical studies of industry practice for in-depth problem understanding. The project aims to design solutions for technical specialization and ecosystem governance. In particular, trade-offs between model size, data needs, computing costs, privacy and secrecy will be addressed.

You will primarily devote yourself to your doctoral programme, which includes participation in research projects as well as third cycle courses, seminars and conferences. Since the project is conducted in the context of the ELLIIT and NextG2Com initiatives, you will interact with corresponding academic and industrial partners.

The work duties include:

• Research within the project topic
• Collaboration with partners in ELLIIT and NextG2Com
• Participation in international research conferences
• Taking third cycle courses
• Participation in teaching and other departmental work (however, a maximum of 20% of working hours).

To be eligible for admission and employment as a doctoral student, you must fulfil the requirements below.

Admission Requirements

A person meets the general admission requirements for third-cycle courses and study programmes if the applicant:

• has been awarded a second-cycle qualification, or
• has satisfied the requirements for courses comprising at least 240 credits of which at least 60 credits were awarded in the second cycle, or
• has acquired substantially equivalent knowledge in some other way in Sweden or abroad.

A person meets the specific admission requirements for third cycle studies in Computer Science if the applicant has:

• at least 60 credits from M.Sc. level courses that are relevant for this topic, or
• an MSc in Engineering in Computer Science and Engineering, Electrical Engineering, Information and Communication Technology, Engineering Physics or Engineering Mathematics.

Additional Requirements

In order to complete the doctoral programme in question, the following are also required:

• very good knowledge of English, spoken and written
• good knowledge about software and AI engineering theory and practice
• good knowledge about machine learning
• ability to collaborate with industry partners
• good written and oral communication skills
• good ability to cooperate
• good ability to work independently and to formulate and tackle research problems.

Other Qualifications (Advantages)

For the doctoral programme in question, the following are considered as other qualifications:

• relevant industrial experience
• working experience as a software engineer
• contributions to open source software, data commons and open source AI models
• knowledge about qualitative research methods
• knowledge about design science research methods

Lund University is a public authority which means that employees get particular benefits, generous annual leave and an advantageous occupational pension scheme.

The employment is a fixed-term employment at full time, starting as soon as possible, however no later than 2026-12-15. Third cycle studies at LTH consist of full-time studies for 4 years. In the case of teaching and other departmental duties, the employment is extended accordingly. Doctoral studentships are regulated in the Higher Education Ordinance (1993:100), chapter 5, 1-7 §§.

Applications shall be written in English and include:

• CV and a personally written cover letter stating the reasons why you are interested in the doctoral programme/employment and in what way the research project corresponds to your interests and educational background.
• Copies of issued study certificates and/or awarded degree certificates. These must confirm that you meet the general and specific admission requirements for the doctoral programme and show that you have the subject knowledge required for the doctoral programme project.
• Other documents you wish to be considered (grade transcripts, contact information for your references, letters of recommendation, etc.)