Ph.D. positions in Computer Science for students holding MSc
Role details
Job location
Tech stack
Job description
In this position students will contribute to research projects in CKL and as part of their education, will also engage in a dedicated 6-months internship period at Constructor Technology (CT), gaining first-hand industrial experience., The appointment provides full financial coverage through a dedicated fellowship, comprising:
- Monthly stipend of €1,650
- Monthly research-cost allowance of €100 (Forschungskostenpauschale)
- Health-insurance subsidy of €100 per month
- Supplementary €550 mini-job allowance to support parallel part-time employment
This structure follows best practices of European research funding programs and ensures that the PI can pursue research objectives with both financial and administrative stability., * Academic transcripts
- A detailed letter of motivation outlining research interests and career goals
- 2 letters of reference
Shortlisted candidates will be invited to interviews. Admission decisions will be announced by December 20, 2025.
Requirements
Do you have experience in Research?, Do you have a Master's degree?, Constructor University, in collaboration with Constructor Knowledge Labs (CKL) and Constructor Technology (industry partner), invites applicants holding MSc degree and with a very strong scientific profile for Ph.D. student positions in the field of Computer Science, with a focus on Artificial Intelligence (AI) and Machine Learning (ML)., * Holding recognized MSc degree (or equivalent) in Computer Science, AI, ML, or a related discipline;
- Hands-on experience with large language models (LLMs) and their applications;
- A track record of publications in AI/ML or related areas;
- Strong skills in academic English writing (peer-reviewed papers, reports, or equivalent);
- Hands-on experience with research, demonstrated through publications and/or open-source contributions;
- Depending on the project strong mathematical background supported with experience in defining and developing knowledge-graph or information retrieval systems.