Assistant Professor in Computing Science with a focus on machine learning

Umeå University; Sweden; On-site; SEK 50,000 - 70,000; Full time

Benefits offered by this job

Wide variety of benefits for work-life balance

Job summary

Umeå University is seeking an Assistant Professor in Machine Learning to join the Department of Computing Science. The position allows for establishing a research group aligned with the Center's theme and has a tenure-track offer built over six years with a focus on research and teaching.

The ideal candidate should have a PhD and experience in independent research, supervise graduate students, and carry out university-level teaching.

Applicants should apply via the Varbi recruitment system before 10 August 2026.

Qualifications

• Experience in conducting independent research in machine learning.
• Ability to effectively supervise and examine students at all education levels.
• Demonstrated scientific productivity in the research community.

Responsibilities

• Supervise doctoral students and postdocs.
• Conduct teaching in machine learning and AI courses.
• Pursue external funding and contribute to the department.

Skills

Independent research in machine learning

Pedagogical expertise

Ability to obtain research funding

Collaboration with community

Education

PhD (or equivalent expertise)

Job description

Assistant Professor – Machine Learning

We are opening a tenure‑track Assistant Professor position in machine learning with employment at the Department of Computing Science. The position offers an opportunity to establish your research group and develop your independent line of research aligned with the Center’s theme.

Responsibilities

The position follows a six‑year fixed‑term appointment, with 75% research and 25% teaching or other meriting tasks. At the end of the period you may apply for promotion to Associate Professor.

The successful candidate will supervise doctoral students and postdocs, conduct teaching of undergraduate and graduate courses in machine learning and AI, and may teach introductory computer science courses. They are expected to pursue external funding, contribute to the department, and collaborate with the surrounding society.

Eligibility Requirements

A PhD (or equivalent expertise within seven years prior to the application deadline) is required. A PhD granted earlier may still be considered only in exceptional circumstances such as sick leave or parental leave.

The applicant should have experience conducting independent research in machine learning.

Assessment Criteria

The main criteria are the degree of research expertise and pedagogical expertise. Administrative and other experience can also be considered.

Scientific Expertise

Scientific expertise shall be demonstrated through independent scientific productivity. Criteria include:

• breadth and depth of research – quality and extent
• originality in research
• productivity
• contributions to the international research community
• commissions of trust within the research community
• ability to competitively obtain research funding
• collaboration with the surrounding community

A high level of competence in machine learning for inference or prediction in complex dynamical systems is of particular importance. Research is expected to be directed toward adaptive mechanisms in living systems under stress within the Center's theme. Previous experience in interdisciplinary work or with living systems is a strong advantage.

Pedagogical Expertise

• ability to plan, implement and evaluate teaching and an ability to supervise and examine students at every level of education
• ability to vary teaching methods and examination forms in relation to anticipated study results and the nature of the subject
• experience of collaboration with the surrounding society in planning and implementation of education
• participation in the development of learning environments, teaching aids and study resources
• a reflective approach to student learning and one’s own role as a teacher

Administrative Expertise

• experiences of supervision (students, postgraduate students, postdoc)
• participation in working groups or committees (department, faculty or university level)
• experiences of collaboration outside the academy
• experience of organizing research and educational activities

  Benefits

  The faculty offers a wide variety of benefits that promote a good work‑life balance.

  Application Process

  Applicants must complete the Varbi application, answering the required questions. The application should be written in English and include the following items:

  1. CV / Application form – the CV must be submitted as a PDF and must provide basic information (contact details, employment history and education), an account of research experience (including a list of articles published and a brief research plan), an account of pedagogical experience and activities, an account of experiences of developing and managing activities and staff, an account of experiences of interacting with the surrounding society and popularizing science, and references with contact details.
  2. Copies of relevant university degrees and diplomas.
  3. Copies of five research publications relevant to the position, numbered according to the publication list.
  4. Attachments to a pedagogical portfolio.

  Applications should be submitted via the e‑recruitment system Varbi and be received no later than 10 August 2026.