Ph.D. Positions in Computer Science (with a focus on AI and ML)

Organization: Constructor University

Location: Bremen Germany

The research group led by Prof. Dr. Alexander Tormasov at Constructor University in collaboration with Constructor Knowledge Institute and Constructor Technology invites applications for Ph.D. positions in the field of Computer Science with the profile in Artificial Intelligence and Machine Learning.

Constructor University is a private research and teaching university (English medium) located in Bremen Germany. Our university maintains a close partnership with Constructor Knowledge Institute and Constructor Technology collaborating on joint research projects. This partnership offers a dynamic and innovative environment where joint PhD students and researchers can engage in impactful applied research in the fields mentioned above.

About the Program

The Ph.D. program at Constructor University is primarily research-based focusing on conducting original research and writing a thesis. The program aims to explore cutting-edge developments in AI and ML as well as their applications in science education healthcare finance and autonomous systems. While the core activity is centered around research and the production of the dissertation students will also have access to a variety of courses (depending on the availability) in advanced research methodologies systems design and technology innovation enabling students to gain both foundational and specialized expertise. Students benefit from access to exclusive datasets collaborations with industry and academic experts and participation in international conferences. They will use the innovative solution created by Constructor Technology for their studies.

Specific Research Themes

• Knowledge Graphs for Scientific Knowledge Representation and Inference
• Large Language Models (LLMs) Reasoning and Mathematics Problem-Solving
• Secure Enterprise AI Models and Encryption Techniques
• On-Premises AI Platforms for Medical Research
• Multi-Scale Foundation Models for Material Science
• Leveraging Artificial Intelligence in Code Development Kernel Operations and Application Design on Unix/Linux Systems
• Workflow and Programming Model Optimization for Scientific Applications
• Encryption algorithms for ML models including for enterprise customers.
• Quantum computing and related AI.

Funding and Work Opportunities

These positions are funded through tuition fees. However fee waivers are available for eligible students through a competitive application process. Applicants are encouraged to apply for these waivers during the admissions process to reduce or eliminate their tuition costs. For full-time students there are additional opportunities to support their studies financially. They may work as teaching assistants or research assistants on projects that are closely aligned with their thesis topics. They may receive salaries designed to cover living expenses. In addition to financial compensation these positions provide opportunities for skill development collaboration with leading researchers and integration into the academic and research community at Constructor Technology.

Applicant Profile

Mandatory

• Applicant holds a MSc degree or equivalent in a relevant field e.g. Computer Science Artificial Intelligence Machine Learning or a related discipline. According to German Higher Education law all degrees earned outside of Germany must be individually assessed to meet the German requirements.
• Applicant should have a publication record / open-source project.
• Strong analytical and technical skills including proficiency in programming and data analysis tools.
• English proficiency

Preferrable

• Applicant is ambitious self-motivated and enjoys working in a collaborative interdisciplinary environment.
• Applicant has a strong interest in AI and ML and is eager to engage in innovative research.
• Applicant possesses excellent analytical and communication skills (including English proficiency) and is open to learning new methods and pursuing collaborations.
• Applicant has relevant experience in research or industry and is willing to participate in educational courses and activities.

Application Details

Candidates are required to submit their application online at The application deadline is February 20 2025 at 13:00 (CEST).

Applicants should include their CV academic transcripts and a detailed letter of motivation outlining their research interests and career goals.

Short-listed candidates will be invited for interviews with admission decisions announced by March 10 2025.