Part-Time AI Research Internship for Master’s Students

NXAI; Linz; On-site; EUR 8,900 - 13,000; Part time

Benefits offered by this job

Mentorship and career development

Direct collaboration with ML experts

Exposure to cutting-edge research

Job summary

NXAI in Linz, Austria, offers a unique part-time internship (20h/week) for Master’s students to join a small elite team at the forefront of AI research. The role starts anytime from January 2027 until August 2027 and involves literature reviews, algorithm implementation, experiments, and documentation.

Successful candidates will collaborate with senior researchers and engineers, receive mentorship, and contribute to real research outputs while advancing their skills in machine learning and

Qualifications

• Enrollment in a Master’s program in AI, Computer Science, Data Science, Mathematics, Physics, or related fields.
• Completion of at least one term of Master’s-level coursework.
• Solid background in machine learning fundamentals and applied mathematics.
• Strong programming skills.
• Ability to communicate results clearly in writing and presentations.
• Self-driven, organized and capable of working both independently and in a team.

Responsibilities

• Contribute to literature reviews and structured state-of-the-art surveys.
• Implement and evaluate algorithms.
• Support experiments, benchmarking and reproducibility checks.
• Document results clearly and provide concise reports.
• Collaborate with researchers in developing and testing hypotheses.
• Prepare short presentations or summaries of findings for internal meetings.

Skills

Machine learning basics

Applied mathematics

Programming proficiency

Communication skills

Independent and team work

Education

Master’s program in AI/CS/Data Science/Math/Physics

Completed at least one term of Master’s coursework

Tools

Python

Job description

NXAI in Linz, Austria, offers a unique part-time internship (20h/week) for Master’s students to join a small elite team at the forefront of AI research. The role starts anytime from January 2027 until August 2027 and involves literature reviews, algorithm implementation, experiments, and documentation.

Successful candidates will collaborate with senior researchers and engineers, receive mentorship, and contribute to real research outputs while advancing their skills in machine learning and