13 PhD positions in knowledge-driven machine learning

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4th March 2024
Languages
English

• English

English
13 PhD positions in knowledge-driven machine learning
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Would you like to take a PhD on knowledge-driven machine learning?

Join Integreat, a Norwegian centre of excellence with a community of ambitious researchers from the fields of machine learning, statistics, logic, language technology, and ethics.

We offer fulltime positions for a period of three years (or four years with 25% service activity, teaching, supervision and/or administrative tasks, depending on the unit of employment). 

Starting date as soon as possible and upon individual agreement. 

About Integreat

Integreat – Norwegian Centre for Knowledge-driven Machine Learning is a Centre of Excellence, funded by the Research Council of Norway. Integreat has two branches, one in Oslo (University of Oslo, UiO) and one in Tromsø (UiT The Arctic University of Norway).

Machine learning is the mathematical and computational engine of Artificial Intelligence (AI), and therefore it is a fundamental force of technological progress in our increasingly digital, data- and algorithm-driven world. Integreat develops theories, methods, models, and algorithms that integrate general and domain-specific knowledge with data, laying the foundations of next generation machine learning. We do this by combining the mathematical and computational cultures, and the methodologies and theories, of statistics, logic, language technology, ethics and machine learning, in new and unique ways.

Focus of Integreat is to develop ground-breaking methods and theories, and therefore solving fundamental problems in science, technology, health and society. Integreat draws on the research strengths of researchers and students from the departments of Mathematics, Informatics, Philosophy, and the Oslo Centre for Biostatistics and Epidemiology at UiO, the Norwegian Computing Centre (NR) and the ML group at UiT, with members from the departments of Physics and Technology, Mathematics and Statistics, and Computer Science. 

Job description

Integreat, the Norwegian centre for knowledge-driven machine learning , is seeking to recruit a group of fulltime PhD students at the University of Oslo and the UiT The Arctic University of Norway for thirteen cross-disciplinary projects across machine learning, statistics, logic, language technology and ethics.  All 13 projects are ambitious, timely, and contributing to a new foundation of machine learning. 

Detailed descriptions of the projects .

Applicants must select and rank up to five projects of interest to them in the application.

As an Integreat PhD Fellow, you will be enrolled in the PhD programme at the University of Oslo (11 projects), or UiT The Arctic University of Norway (2 projects). Place of employment is specified in each project description. Bosch Centre for Artificial Intelligence , Germany is a partner of this call, and will fund and employ candidates for two of the projects. All of the recruited candidates will be part of the Integreat research community and you are expected to participate in the centre’s activities. 

You will all join a vibrant community of scientists, from young talents to established researchers, across machine learning, statistics, logic, language technology and ethics. By recruiting a large cohort of young PhD students, Integreat’s aim is to train a community of early career researchers, to become the next generation of scientists of modern knowledge-driven machine learning. 

Working language: English. 

Applicants are required to review general qualification requirements, project specific requirements, and PhD programme admissions requirements before applying. 

PhD projects 

Available PhD projects are listed below. Links include a scientific description, the team of supervisors and specific qualification requirements.

• Project 1: Statistical models and logic: handling inconsistencies
  • Employment: University of Oslo, Department of Mathematics
  • PhD programme: University of Oslo, Faculty of Mathematics and Natural Sciences
• Project 2: Sparse models for machine learning from a Bayesian viewpoint
  • Employment: University of Oslo, Department of Mathematics
  • PhD programme: University of Oslo, Faculty of Mathematics and Natural Sciences
• Project 3: Developing novel information theoretic discrepancy measures
  • Employment: UiT - The Arctic University of Norway, Department of Physics and Technology
  • PhD programme: UiT - The Arctic University of Norway, Faculty of Science and Technology
• Project 4: Exploration and control of the inner representation in generative AI models
  • Employment: UiT -The Arctic University of Norway, Department of Physics and Technology
  • PhD programme: UiT -The Arctic University of Norway, Faculty of Science and Technology
• Project 5: Structure-generating models for transition metal complexes
  • Employment: University of Oslo, Department of Mathematics
  • PhD programme: University of Oslo, Faculty of Mathematics and Natural Sciences
• Project 6: Benchmarking ethical reasoning in Large Language Models
  • Employment: University of Oslo, Department of Informatics
  • PhD programme: University of Oslo, Faculty of Mathematics and Natural Sciences
• Project 7: Discrepancy measures and accelerated likelihood-free inference for simulator-based models
  • Employment: University of Oslo, Oslo Centre for Biostatistics and Epidemiology, Institute of Basic Medical Sciences
  • PhD programme: University of Oslo, Faculty of Medicine
• Project 8: Knowledge and bias extraction from Large Language Models
  • Employment: University of Oslo, Department of Informatics
  • PhD programme: University of Oslo, Faculty of Mathematics and Natural Sciences
• Project 9: Embedded sufficient statistics
  • Employment: University of Oslo, Department of Informatics
  • PhD programme: University of Oslo, Faculty of Mathematics and Natural Sciences
• Project 10: Multi-modal data integration for personalized treatment recommendations
  • Employment: University of Oslo, Oslo Centre for Biostatistics and Epidemiology, Institute of Basic Medical Sciences
  • PhD programme: University of Oslo, Faculty of Medicine
• Project 11: Learning differential models (and other logic rules) from data with uncertainty
  • Employment: University of Oslo, Oslo Centre for Biostatistics and Epidemiology, Institute of Basic Medical Sciences
  • PhD programme: University of Oslo, Faculty of Medicine
• Project 12: Scalable and knowledge-driven identification of anomalous structure in evolving data stream settings
  • Employment: Bosch Centre for Artificial Intelligence, Germany
  • PhD programme: University of Oslo, Department of Mathematics, Faculty of Mathematics and Natural Sciences
• Project 13: Uncertainty quantification in the presence of logical constraints
  • Employment: Bosch Centre for Artificial Intelligence, Germany
  • PhD programme: University of Oslo, Department of Informatics, Faculty of Mathematics and Natural Sciences

via Unsplash
Qualification requirements

Integreat aims at recruiting independent, motivated, and highly talented students, who have a master’s degree, or are in the finalising phase of writing their master thesis. Candidates without a master’s degree must complete the final exam of their master studies by 30 June 2024.

Qualification requirements include general and project specific. Apply only for up to five projects where you fully satisfy all requirements (general, project specific and the PhD programme admission requirements).

Required qualifications for all applicants: 

• Obtained a master's degree (total 120 ECTS) or currently working on finalising their master thesis (at least 30 ECTS) in an area relevant to Integreat, or a foreign degree (M.Sc.-level) corresponding to a minimum of four years in the Norwegian educational system.
• Candidates without a master’s degree must complete the final exam of their master studies by 30 June 2024.
• Research interest in knowledge-driven machine learning, in at least one of its contributing fields of statistics, logic, language technologies, ethics, or machine learning.
• Excellent oral and written skills in English.

 

Project specific requirements:

Each project has specific requirements, in addition to the general ones stated above. These are obligatory. Review project specific requirements in the detailed descriptions of the projects . 

Grade requirements for admission to PhD programmes

Applicants must have good academic records to be enrolled as PhD Fellows at UiO and UiT: 

• The average grade point for courses included in the bachelor’s degree must be C or better (scale of the Norwegian educational system).  

For University of Oslo projects

• The average grade point for courses included in the master’s degree must be B or better in the Norwegian educational system. The master´s thesis must have the grade B or better in the Norwegian educational system, also for theses submitted after the deadline of this call. 

For UiT The Arctic University of Norway projects

• 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. To gain admission to the PhD 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 .

Further information on admission requirements to PhD programmes

All fellowships require admission to the PhD programme at the unit of employment. For the Bosch positions, PhD fellows are required to follow the PhD programme at the University of Oslo, Faculty of Mathematics and Natural Sciences.

University of Oslo

The purpose of the fellowship is research training leading to the successful completion of a PhD degree. The fellowship requires admission to the PhD programme at the Faculty of Mathematics and Natural Sciences or the Faculty of Medicine, depending on the project and unit of employment. The application to the PhD programme must be submitted to the respective department no later than two months after taking up the position.

For more information see:

• http://www.uio.no/english/research/phd/
• https://www.mn.uio.no/english/research/phd/ (Faculty of Mathematics and Natural Sciences)
• https://www.med.uio.no/english/research/phd/ (Faculty of Medicine)

 

UiT The Arctic University of Norway

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 .

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.

• Regulations and policies at UiT The Arctic University of Norway
• PhD at UiT The Arctic University of Norway | UiT

Personal skills

We seek candidates who:

• Are highly motivated, open-minded, academically strong, creative, and curious.  
• Have the ability to work independently, as well as in a team environment.  
• Have strong analytical and problem-solving abilities.  
• Have strong written and verbal communication skills. 

In assessing the candidates, particular emphasis will be placed on academic qualifications, the candidates’ fit within the overall research programme, and personal motivation to proceed a PhD on the selected project within Integreat. 

via Unsplash
We offer

For employment at UiO and UiT:

• Salary NOK 532 200 – 575 400 per year depending on qualifications and seniority as PhD Research Fellow (position code 1017). 
• A unique research environment with multiple opportunities to develop research themes at the forefront of modern science.
• A friendly professional and stimulating international working environment. 
• Access to a network of top-level national and international collaborators. 
• A reliable and generous pension agreement.
• Good welfare schemes. 
• Full access to public health services through membership of the National Insurance Scheme. 
• A vibrant international academic environment.  
• Career development programmes at the faculties and individual professional plan for the full duration of the doctoral research period. 
• Research mobility funds for shorter stays. 
• Oslo’s and Tromsø’s family-friendly surroundings with their rich opportunities for culture and outdoor activities.

 

For employment at Bosch Centre for Artificial Intelligence, Renningen, Germany:

For further information on evaluation of applicants and employment conditions, see the project descriptions (Projects number 12 and 13 ).

How to apply

For the University of Oslo and UiT The Arctic University of Norway positions 

Candidates must only apply once through the application electronic recruiting portal. To be considered for the employment, you must include all required documents in English or in a Scandinavian language. 

Applications sent by email for positions (Projects 1-11) will not be considered.

The application with attachments must be delivered in our electronic recruiting system by the deadline (23:59 Norwegian time). Foreign applicants are advised to attach an explanation of their University's grading system. Interviews with the best qualified candidates will be arranged.

The application must include:

• SURNAME-Pdf-1: CV
  • Summarising education, positions, name of supervisors and relevant academic work – list of relevant scientific publications (if any).
• SURNAME-Pdf-2: Cover letter
  • a) include the ranked list of PhD projects of interest among the ones listed here (not more than five)
  • b) state reasons and motivations for pursuing a PhD at Integreat;
  • c) describe relevant scientific competences and experiences, research interests, and future career objectives.
• SURNAME-Pdf-3: Your master’s thesis/ draft version or parts of the master’s thesis (link or pdf) if available.
  • If you are in the finalising phase of completion of your master's degree, you may still apply and submit a draft version of your thesis with a statement from yourself or from your supervisor or institution indicating when the degree is expected to be obtained. Obtained master’s degree is required before commencement in the position.
• SURNAME-Pdf-4: List of 2-3 references (at least one of them in a supervising position). 
• SURNAME-Pdf-5: Copies of official transcript of grades for all bachelor’s and master’s courses.
  • These should also include full course titles. If you have not finished your master, you must submit your current transcripts for the courses taken in your master study.
• SURNAME-Pdf-6:
  • Copy of diploma for bachelor's degree
  • Copy of diploma for master's degree (if already obtained).
• SURNAME-Pdf-7: Documentation of English proficiency
  • For University of Oslo projects: https://www.mn.uio.no/english/research/phd/regulations/regulations.html#toc8
  • For UiT The Arctic University of Norway positions: https://www.samordnaopptak.no/info/english/language-requirements/

 

For the Bosch positions (exclusively projects 12 and 13)

If you are applying only for the Bosch positions and if you are not interested in any of the positions at University of Oslo and UiT The Arctic University of Norway, submit the same package of documents as listed above, following the same instructions, to [email protected] by the set deadline (23:59 Norwegian time) of this call. Do not use the electronic portal.

If an applicant is interested in projects at both UiO/UiT and Bosch, apply only through the electronic portal.

Formal regulations

University of Oslo

Please see the guidelines and regulations for appointments to Research Fellowships at the University of Oslo.

According to the Norwegian Freedom and Information Act (Offentleglova) information about the applicant may be included in the public applicant list, also in cases where the applicant has requested non-disclosure.

UiO has an agreement for all employees , aiming to secure rights to research results a.o.

Inclusion and diversity are a strength. The University of Oslo has a personnel policy objective of achieving a balanced gender composition. Furthermore, we want employees with diverse professional expertise, life experience and perspectives.

If there are qualified applicants with disabilities, employment gaps or immigrant background, we will invite at least one applicant from each of these categories to an interview.

UiT The Arctic University of Norway

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. 

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 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 nondisclosure. You will receive advance notification in the event of such publication, if you have requested non-disclosure.

Contact information

For further information about the positions please contact: 

• General inquiries: Integreat Administrative Leader Maria Dikova [email protected] , +4722858898 and Integreat Centre Director Arnoldo Frigessi [email protected]
• Inquiries on UiT Tromsø positions, Inger Solheim: [email protected] +47 77 64 44 65
• For inquiries regarding specifically a research project, please contact the supervisor named as point of contact in the project description.

For questions regarding Jobbnorge, please contact HR Adviser Ole Rustad at University of Oslo: [email protected] .

via Unsplash
About Integreat

Integreat is a Centre of Excellence, funded by the Research council of Norway. Integreat has two branches, one in Oslo (University of Oslo, UiO) and one in Tromsø (UiT The Arctic University of Norway). Machine learning is the mathematical and computational engine of Artificial Intelligence (AI), and therefore a fundamental force of technological progress in our increasingly digital, data- and algorithm-driven world.

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 by combining the mathematical and computational cultures, and the methodologies and theories, of statistics, logic, language technologies, ethics and machine learning, in new and unique ways.

Focus of Integreat is to develop ground-breaking methods and theories, and by this solving fundamental problems in science, technology, health and society. Integreat draws on the research strengths of researchers and students from the departments of Mathematics, Informatics, Philosophy, and the Oslo Centre for Biostatistics and Epidemiology at UiO, the Norwegian Computing Centre (NR) and the ML group at UiT, with members from the departments of Physics and Technology, Mathematics and Statistics, and Computer Science.

Questions about the position

Maria Dikova

Administrative Leader

[email protected]

Arnoldo Frigessi

Centre Director

[email protected]

Inger Solheim

Project Coordinator UiT

[email protected]

Apply for this job
Deadline

4th March 2024

Employer

Integreat -Norwegian Centre for Knowledge-driven Machine Learning

Municipality

Oslo
Tromsø - Romsa

Scope

Fulltime (13 positions) Fulltime (%)

Duration

Temporary

Place of service
Moltke Moes vei 35, 0851 Oslo
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