PhD Fellow in the intersection of information theory and deep learning

The position

A PhD position is available at the Department of Physcis and Technology, Faculty of Science and Technology The SFF Integreat announces one vacant PhD position in the intersection of the research topics information theory and deep learning.

The position is for a period of four years. The nominal length of the PhD programme 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 a PhD program is a prerequisite for employment. The workplace is at UiT in Tromsø. You must be able to start in the position in Tromsø within a reasonable time after receiving the offer. Preferred starting date is in January 2025, but earlier dates can also be discussed.

The studentship affiliation

The successful candidate will work at the research centre Integreat at the Department of Physics and Technology. The Centre is a Norwegian Centre of Excellence, funded by the Research Council of Norway.

Integreat aims to shape the new field of knowledge-driven machine learning in Norway. Our research makes machine learning more sustainable, accurate, trustworthy, and ethical. Unlike the current focus on data-centric approaches in machine learning, Integreat develops theories, methods, models, and algorithms that integrate general and domain-specific knowledge with data, laying the foundations of next generation machine learning. This will be done through interdisciplinary work that combines the mathematical and computational cultures, and the methodologies of statistics, logic, and machine learning in unique ways. Integreat's machine learning will solve fundamental problems in science, technology, health, and society, and contribute to make Norway a world leading country in AI.

The position’s field of research

The focus of this PhD fellowship lies on method development in the intersection between information theory and deep learning. The PhD student will focus on exploiting the knowledge that neural networks have inherent structures that can be used to improve information theoretic measurements.

The core of the position will be focused on designed estimator of information theoretic measures in the context of deep learning. Information theory is a key tool in the field of deep learning, and is used extensively in loss functions, analysis, regularization, and numerous other purposes. Particularly for analysis, information theory has been used as a critical tool to understand the generalization properties of deep learning algorithms, and this will be an important focus area for the position. Despite the great potential of information theory for understanding deep learning, there are many challenging aspects related to estimating information theoretic quantities in deep learning. This position will aim to make significant advances when it comes to tackling these challenges, and by doing so deepen the understanding of the highly active field of research that is deep learning.

We expect that you will engage in collaborative research with other members of the Integreat centre and the Machine learning research group, across partners and innovation areas. Integreat is a highly interdisciplinary center, and we also expect you to engage with researchers from fields ranging from machine learning, statistics, and mathematics, to name a few

Contact

For further information about the position, please contact Associate Professor Kristoffer Wickstrøm:

• phone:+47 776 23216
• email: kristoffer.k.wickstrom@uit.no

Qualifications

We are looking for a motivated candidate who is independent thinking and enjoys working in a team. The suitable candidate should have expertise in information theory and deep learning and have a strong documented background in mathematics. Special emphasis will be given to candidates with prior experience in the above-mentioned topics.

This position requires a Norwegian master's degree in physics, mathematics/statistics, computer science, or similar, or a corresponding foreign master’s degree recognized as equivalent to a Norwegian master's degree. If you are near completion of your master’s degree, you may still apply.

You must document significant coursework in machine learning, pattern recognition, statistics, deep learning, and programming skills. Coursework in signal processing and physics will be considered a plus.

If your master’s thesis had a strong element of mathematical modelling for development of neural networks, this will be considered a big advantage. Experience with analysis of spatio-temporal medical image data and interdisciplinary collaboration with clinicians will be considered a plus. Since the project will revolve around neural network research, experiences with software tools such as PyTorch/Tensorflow are qualifications we are looking for. Qualifications in terms of relevant publications for this position will be weighted positively.

We will also emphasize motivation and personal suitability for the position. We are looking for candidates who demonstrate:

• Independence and self-motivation
• Creativity and ability to think outside the box
• Excellent work ethics and commitment to the job

Applicants must document fluency of in English and be able to work in an international environment.Nordic applicants can document their English capabilities by attaching their high school diploma.

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 program may be given consideration.

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 in the PhD position, you must be qualified for admission to the PhD programme at the Faculty 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, or an integrated master's degree.

UiT normally accepts higher education from countries that are part of the Lisbon Recognition Convention.

In order to gain admission to the programme, the applicant must have a grade point average of C or better for the master’s degree and for relevant subjects of the bachelor’s degree. A more detailed description of admission requirements can be found here.

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 from NOKUT. 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.

If you are employed in the position, you will be provisionally admitted to the PhD programme. Application for final admission must be submitted no later than two months after taking up the position.

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.

We offer

• We offer an interesting project within a highly innovative centre environment
• Opportunities to travel and meet other leading scientists within the field
• A fantastic work environment with nice colleagues
• Good career opportunities
• Flexible working hours and a state collective pay agreement
• Pension scheme through the state pension fund
• PhD Fellows are normally given a salary of 532 200 NOK/year with a 3% yearly increase

You will work from Tromsø, a lively town with approximately 78.000 inhabitants. It is known for its beautiful scenery, northern lights, midnight sun, as well as being the northernmost university in the world and well connected to the rest of Europe. Located on an island surrounded by fjords and mountains, Tromsø is a major cultural hub within the Arctic Circle and a great spot for outdoor activities (hiking, skiing, etc.

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.

More practical information about working and living in Norway can be found here: https://uit.no/staffmobility

Application

Your application must include:

• Cover letter explaining your motivation and highlighting your background and its relevance to the announced position
• CV (containing a complete overview of education, supervised professional training and professional work)
• Diploma for bachelor's and master's degree
• Transcript of grades/academic record for bachelor's and master's degree
• Explanation of the grading system for foreign education (Diploma Supplement if available)
• Documentation of English proficiency
• 3 references with contact information, preferably including the master thesis supervisor
• Master’s thesis (or draft master thesis if it is not completed), 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 not in English or Scandinavian. If English proficiency is not documented in the application, it must be documented before starting in the position. We only accept applications and documentation sent via Jobbnorge within the application deadline.

General information

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

Remuneration for the position of PhD Fellow is in accordance with the State salary scale code 1017. 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 PhD Fellow has already completed parts of their research training programme or when the appointment is based on a previous qualifying position PhD Fellow, research assistant, or the like in such a way that the total time used for research training amounts to three years.

We process personal data given in an application or CV in accordance with the Personal Data Act (Offentleglova). According to the Personal Data Act information 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.