PhD in Computer Science: Software Waste Detection and Reduction in AI-assisted DevOps
PhD opportunity in Computer Science at Lund University
focused on
software waste detection and reduction
in
AI-assisted DevOps
for complex software systems.
The position is part of the
ELLIIT-funded WasteNoMore project
, a collaboration between
Lund University
and
Linköping University
. The project studies how to detect and reduce software development waste in large-scale development and operations workflows, especially in
cloud-edge systems
,
microservice architectures
, and other complex software-intensive systems. The research combines sustainability-driven software engineering with AI tools such as large language model assistants, runtime monitoring, design space exploration, and empirical software engineering methods.
The doctoral student will be based at the
Department of Computer Science
, Lund University, within the Software Development and Environments unit, and will also interact with the
NEXTG2COM
industrial competence center. The work includes research, third-cycle courses, seminars, conferences, collaboration with academic and industrial partners, and up to 20% teaching/departmental duties.
Eligibility:
a second-cycle degree or equivalent, plus specific Computer Science admission requirements such as relevant advanced credits or an M.Sc. in a related engineering field. Strong English, communication, software engineering knowledge, programming skills, independence, and collaboration ability are required. Experience in software engineering, AI systems, software development tools, or human-computer interaction is considered an advantage.
Funding and employment:
this is a
full-time employed doctoral position
at Lund University, funded through ELLIIT. The appointment is fixed-term for 4 years, with extension possible for teaching and other duties. Salary is monthly; no stipend amount is specified.
Application deadline:
2026-04-20. Applications must be written in English and include a CV, cover letter, degree/study certificates, and any additional supporting documents such as transcripts or references.
