PhD Fellow in Knowledge-Driven Machine Learning

Arbeidsplassen; Tromsø; On-site; NOK 550,000 - 634,000; Full time

Job summary

A leading research university in Tromsø seeks a PhD Fellow in Knowledge-Driven Machine Learning. The role involves advancing research in machine learning, engaging in collaborative research, and contributing to scientific publications. Candidates should have a master's in a relevant field, strong programming skills in Python, and a background in deep learning. This position offers a salary of 550,800 NOK/year and a vibrant academic environment.

Benefits

Flexible working hours

State collective pay agreement

Pension scheme through the state fund

Qualifications

• Strong formal course background in deep learning and machine learning.
• Documented strong programming skills, preferably in Python.
• Fluency in English in an international environment.

Responsibilities

• Conduct research in knowledge-driven machine learning.
• Develop computational models and algorithms.
• Publish results in peer-reviewed journals.

Skills

Deep learning techniques

Python programming

Machine learning methodologies

Analytical problem solving

Creative initiative

Education

Norwegian master’s degree or equivalent in relevant disciplines

Bachelor's degree of 180 ECTS

Tools

PyTorch

TensorFlow

Jax

Job description

PhD Fellow in Knowledge-Driven Machine Learning

PhD Fellow in Knowledge-Driven Machine Learning

The position is for a period of four years. The nominal length of the PhD program is three years. The fourth year is distributed as 25 % each year and will consist of teaching and other duties. The objective of the position is to complete research training to the level of a doctoral degree. Admission to the PhD programme is a prerequisite for employment, and the programme period starts on commencement of the position.

The workplace is at UiT in Tromsø. You must be able to start in the positionwithin a reasonable time after receiving the offer.

The project

The objective of this position is to advance research in knowledge-driven machine learning, specifically focusing on the research themes of Integreat , at the intersection of Machine Learning, Statistics, Logics, Natural Language Processing, and structured knowledge representations. As a researcher within Integreat, you will contribute to developing next-generation Machine Learning for advanced data analysis, addressing challenges such as interpretability, learning efficiency, and reasoning.

Potential research directions include:

• Designing knowledge-infused learning methods that integrate external ontologies, rules, and curated databases into deep models, enhancing accuracy, interpretability, and robustness.
• Probing and steering the internal mechanisms of deep models by aligning their representations with human-interpretable concepts and formal logical or statistical abstractions, enabling transparent, verifiable reasoning.
• Developing principled methodologies to evaluate and improve the robustness and reliability of knowledge-driven models, leveraging Bayesian statistics and causal inference for calibrated uncertainty, distribution-shift detection, and safety guarantees.

You will be will working within the Center of Excellence Integreat and be affiliated with the UiT Machine Learning Group, benefiting from a vibrant community of early career researchers and expert collaborators. The work will involve collaboration with the Integreat community whose members are in Tromsø and Oslo.

Your role as a PhD Fellow

You will be an integral part of Integreat via the UiT Machine Learning Group. You will engage in
collaborative research with other members of the center and the group. Your specific research tasks
will include:

• Conducting research in knowledge-driven machine learning.
• Developing and implementing computational models and algorithms. Analyzing results and contributing to scientific publications in peer-reviewed journals (expected 3 papers), presenting at meetings and international conferences.
• Taking part in the teaching as teaching assistant at UiT (25% of the PhD time)
• Finally, writing up and defending a PhD thesis.

Want to know more about the position?

For further information about the position, please contact:

• A Norwegian master’s degree (or equivalent) in a relevant discipline, such as: machine learning, computer science, mathematics, statistics, physics, or electrical engineering. If you are near completion of your master’s degree, you may still apply.
• A strong formal course background in deep learning and machine learning in general, or relevant topics such as:
  • neural networks
  • self-supervised learning
  • convolutional neural networks
  • transformer-based networks
  • graph-based approaches
  • Bayesian learning
  • information theory
• Documented strong programming skills (preferably Python), for example with contributions to open-source projects, with an active Github account.
• Documented fluency in English and ability to work in an international environment. Nordic applicants can document their English capabilities by attaching their high school diploma.
• Fulfillment of the requirements for admission to the PhD program (next section)

Desired skills include:

• Research experience via Master's thesis or internships involving the development of deep learning and machine learning methodology and applications
• Experience with software tools such as PyTorch, Keras, Tensorflow, and Jax
• Any relevant scientific publications
• Abilities to be creative and able to take on and develop own initiatives

In the assessment, the emphasis is on the applicant's potential to complete a research education based on the master's thesis or equivalent, and any other scientific work. In addition, other experience of significance for the completion of the doctoral programme may be given consideration. We will also emphasize motivation and personal suitability for the position, including:

• High self-motivation
• Ability to work independently
• Great analytical and problem-solving skills

As many people as possible should have the opportunity to undertake organized research training. If you already hold a PhD or have equivalent competence, we will not appoint you to this position.

Admission to the PhD programme

For employment inthePhD position,you must be qualified for admission to the PhD programmeat theFaculty of Science and Technology and participate in organized doctoral studies within the employment period.

Admission normally requires:

• A bachelor's degree of 180 ECTS and a master's degree of 120 ECTS, or an integrated master's degree of 300 ECTS.

In order to gain admission to the programme, the candidate must document sufficient potential for research. The applicant must have a grade point average of C (strong 3.0) or better for the master’s degree, which must contain an independent work. A more detailed description of admission requirements can be foundhere .

If you are employed in the position, you willbeprovisionally admittedto the PhD programme. Application forfinal admissionmust be submitted no later thantwo monthsafter taking up the position.

Applicants with a foreign education will be subjected to an evaluation of whether the educational background is equal to Norwegian higher education, following national guidelines fromNorwegian Directorate for Higher Education and Skills . Depending on which country the education is from, one or two additional years of university education may be required to fulfil admission requirements, e.g. a 4-year bachelor's degree and a 2-year master's degree. UiT normally accepts higher education from countries that are part of the Lisbon Recognition Convention.

We offer

• An exciting research project at the forefront of knowledge-driven machine learning.
• An internationally leading and welcoming academic environment with dedicated colleagues.
• A fantastic, lively work environment in the cosy hometown of Tromsø, surrounded by the stunning landscape of Northern Scandinavia.
• Flexible working hours and a state collective pay agreement
• Pension scheme through the state pension fund
• PhD Fellows are normally given a salary of 550 800 NOK/year with a 3% yearly increase
• If you have to relocate to Tromsø then theFaculty of Science and Technology may reimburse your moving costs. Further details regarding this matter will be made available if you receive an offer from us.

Norwegian health policy aims to ensure that everyone, irrespective of their personal finances and where they live, has access to good health and care services of equal standard. As an employee you will become member of the National Insurance Scheme which also include health care services.

• An introduction and motivation letter (max 1-2 pages), including an explanation of why you are interested in this research topic and why you are the right candidate for the position.
• CV (max 2 pages).
• Diplomaforbachelor's andmaster's degree
• Official transcripts of grades/academic record forbachelor's andmaster's degree
• Explanation of the grading system for foreign education(Diploma Supplement if available)
• Master’sthesis, and any other academic works

Qualification with a master’s degree is required before commencement in the position. If you are near completion of your master’s degree, you may still apply and submit a draft version of the thesis and a statement from your supervisor or institution indicating when the degree will be obtained. You must still submit your transcript of grades for the master’s degree with your application.

All documentation to be considered must be in a Scandinavian language or English. Diplomas and transcripts must also be submitted in the original language, if notinEnglish or Scandinavian.If English proficiency is not documented in the application, it must be documented before starting in the position. We only accept applicationsand documentationsent viaJobbnorge within the application deadline.

Inclusion and diversity

UiT The Arctic University of Norway is working actively to promote equality, gender balance and diversity among employees and students, and to create an inclusive and safe working environment. We believe that inclusion and diversity are a strength, and we want employees with different competencies, professional experience, life experience and perspectives.

If you have a disability, a gap in your CV or immigrant background, we encourage you to tick the box for this in your application. If there are qualified applicants, we invite at least one in each group for an interview. If you get the job, we will adapt the working conditions if you need it. Apart from selecting the right candidates, we will only use the information for anonymous statistics.

Generalinformation

The appointment is made in accordance with State regulations and guidelines at UiT. At our website, you will find moreinformation for applicants .

The engagement is to be made in accordance with the acts relating to Control of the Export of Strategic Goods, Services and Technology. Candidates who by assessment of the application and attachment are seen to conflict with the criteria in the latter law will be prohibited from recruitment.

After the appointment you must assume that there may be changes in the area of work.

Remuneration for the position of PhDFellowis in accordance with the State salary scale code1017.A compulsory contribution of 2 % to the Norwegian Public Service Pension Fund will be deducted. You will become a member of the Norwegian Public Service Pension Fund, which gives you many benefits in addition to a lifelong pension: You may be entitled to financial support if you become ill or disabled, your family may be entitled to financial support when you die, you become insured against occupational injury or occupational disease, and you can get good terms on a mortgage. Read more about your employee benefits at: spk.no .

A shorter period of appointment may be decided when the PhDFellowhas already completed parts of their research training programmeor when the appointment is based on a previous qualifying position PhDFellow, research assistant, or the like in such a way that the total time used for researchtraining amounts to three years.

We process personal data given in an application or CV in accordance with the Personal Data Act (Offentleglova). AccordingtothePersonal Data Actinformation about the applicant may be included in the public applicant list, also in cases where the applicant has requested non-disclosure. You will receive advance notification in the event of such publication, if you have requested non-disclosure.

Assessment

The applicants will be assessed by an expert committee. The committee's mandate is to undertake an assessment of the applicants' qualifications based on the written material presented by the applicants, and the detailed description draw up for the position. A copy of the assessment report will be sent to all applicants.

The applicants who are assessed as best qualified will be called to an interview. The interview should among other things, aim to clarify the applicant’s motivation and personal suitability for the position.

Om bedriften

UiT The Arctic University of Norway is a multi-campus comprehensive university at the international forefront. Our vision is to be a driving force for developing the High North. The Northern Sami notion eallju, which means eagerness to work, sets the tone for this motive power at UiT. Along with students, staff and the wider community, we aim to utilise our location in Northern Norway and Sápmi, our broad and diverse research and study portfolio and interdisciplinary advantage to shape the future.

Our social mission is to provide research-based education of high quality, perform artistic development and carry out research of the highest international quality standards in the entire range from basic to applied. We will convey knowledge about disciplines and contribute to innovation. Our social mission unites UiT across various studies, research fields and large geographical distances. This demands good cooperation with trade and industry and civil society as well as with international partners. We will strengthen knowledge-based and sustainable development at a regional, national and international level.

Academic freedom and scientific and ethical principles form the basis for all UiT’s activities. Participation, co-determination, transparency and good processes will provide the decision-making basis we need to make wise and far-sighted priorities. Our students and staff will have the opportunity to develop their abilities and potential. Founded on academic integrity, we will be courageous, committed and generous in close contact with disciplines, people and contemporary developments.

We will demonstrate adaptability and seek good and purposeful utilisation of resources, so we are ready to meet the expectations and opportunities of the future. We will strengthen the quality and impact of our disciplines and core tasks through the following three strategic priority areas.