Doctoral Student in AI Engineering and Software Systems
Join a leading research unit at Lund University to explore AI engineering trade-offs in B2B contexts and open-source AI systems.
Best for:Best for recent MSc graduates in computer science or related fields with strong AI/ML and software engineering expertise, keen to explore empirical research in AI systems and industry-academia collaboration.
Overview
This doctoral position at Lund University’s Department of Computer Science focuses on AI engineering, specifically the trade-offs between general and specialized AI models in business-to-business (B2B) contexts and open-source AI ecosystems. The research will be conducted within the Software Engineering unit, a global leader in empirical software engineering, with a focus on MLOps, datacentric AI, and ethical AI. The doctoral student will collaborate with industry partners through the ELLIIT and NextG2Com initiatives, addressing challenges like model performance, energy consumption, and data integrity. The role involves independent research, participation in international conferences, and teaching (up to 20% of time). The position is funded for a fixed-term period, with a focus on developing critical thinking, research ethics, and interdisciplinary collaboration.
What you'll do
- Conduct independent research on AI engineering trade-offs, focusing on general vs. specialized AI models in B2B contexts and open-source ecosystems.
- Collaborate with academic and industrial partners through ELLIIT and NextG2Com initiatives.
- Participate in international research conferences and publish findings in peer-reviewed venues.
- Enroll in third-cycle courses, seminars, and doctoral training programs at Lund University.
- Engage in teaching and departmental work (limited to 20% of working hours).
- Develop leadership, pedagogical, and research ethics skills throughout the doctoral programme.
- Perform empirical studies of industry practices to inform AI engineering solutions.
Requirements
Degree required: A second-cycle qualification (MSc or equivalent) in Computer Science, Engineering in Computer Science and Engineering, Electrical Engineering, Information and Communication Technology, Engineering Physics, or Engineering Mathematics, or at least 60 credits from MSc-level courses relevant to AI engineering.
Degree offered: PhD
Language: English; very good spoken and written proficiency (no specific test score mentioned)
Instruction: English
- Very good written and spoken English proficiency
- Strong theoretical and practical knowledge of software and AI engineering
- Advanced knowledge of machine learning principles and techniques
- Ability to collaborate effectively with industry partners
- Strong written and oral communication skills
- Independent problem-solving and research formulation abilities
- Good teamwork and cooperation skills
- Must meet general admission requirements for third-cycle courses in Sweden (second-cycle qualification or equivalent).
- Must meet specific admission requirements for Computer Science doctoral studies (MSc-level credits or equivalent degree).
- No nationality or residency restrictions mentioned.
Funding & terms
How to apply
Deadline: 2026-12-15
Submit an application in English via the university’s portal, including a CV, cover letter explaining your interest and fit for the project, copies of degree certificates, and any additional documents like transcripts or reference letters.
- CV
- Cover letter
- Copies of issued study certificates or degree certificates
- Transcripts showing subject knowledge for the doctoral programme
- Additional documents (e.g., reference letters, grade transcripts)
Contact
Not specified (contact via application portal)· Doctoral admissions office
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