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Associate Professor/Professor in Machine Learning
UiT Norges arktiske universitet
Hansine Hansens veg18, 9019 TROMSØ
10. desember 2024
UN
Associate Professor/Professor in Machine Learning
UiT Norges arktiske universitet
TROMSØ
10. desember 2024
Om stillingen
The Department of Physics and Technology has up to three open permanent positions as Associate Professor and/or Professor. Early career scientists, with a promising CV, as well as experienced candidates are invited to apply, respectively for Associate and full Professor.
The faculty members will join the UiT Machine Learning Group. The group is internationally recognized, with research ranging from foundational machine learning methodology and algorithms to applied AI development. The range of applications is wide, with a particular focus on healthcare. The new faculty members shall further strengthen the scientific excellence and high-profile of the group, notably in the Centre of Research-based Innovation SFI Visual Intelligence, which is headed by the group, and the Centre of Excellence SFF Integreat – The Norwegian Centre for Knowledge-based Machine Learning.
The workplace is at UiT in Tromsø. You must be able to start in the position in Tromsø within 6 months after receiving the offer.
You have a strong desire to develop the next generation machine learning methodologies. You find motivation by extracting knowledge from ever-increasing and challenging data, such as images, time series, tabular data, or other sources. You understand the importance of gaining insight, creating value, and solve real world applications of value to humankind and towards the UN sustainability goals. You find joy in teaching and you hold high ethical standards of your research, teaching and innovations.
Your interests are in neural networks research, where key research challenges are learning from limited data, interpretability and XAI, uncertainty quantification, and the integration of prior knowledge and context, or in general within self-supervised learning, unsupervised learning, representation learning, generative AI, graph-based learning, information theoretic learning, and/or neural knowledge-based learning. The Machine Learning Group has an internationally recognized expertise in developing theoretical and conceptual aspects of machine learning. This is strengthened by the recent centre of excellence SFF Integreat, where the group plays a major role.
Within the UiT Machine Learning Group and the SFI Visual Intelligence centre, the main applications are within health and medicine. Our research contributes to diagnosis and decision support by extracting patient-specific information from electronic health records and through medical computer vision for important clinical tasks such as cancer characterization. You can help transform healthcare for future needs, with AI as an integral part. Other relevant application areas include marine sciences for abundance estimation and sustainable harvest of the oceans, as well as environmental monitoring. Through machine learning, we can aid the climate, the oceans and Earth.
As a faculty member in the UiT Machine Learning Group, you will have the chance to make an impact on the world and to help shape the future of society with better machine learning solutions that are trustworthy and ethically sound. You are expected to collaborate with the current members in the group. The UiT Machine Learning Group relies strongly on teamwork and joint supervision of students. If you are applying for the Full Professor position, you are expected to bring your network of national and international collaborations and engage them in new connections with the group members.
Further information about the position and UiT is available by contacting:
Head of Machine Learning Group, Associate Professor Benjamin Ricaud; benjamin.ricaud@uit.no
Director of Visual Intelligence and Co-Director of Integreat, Professor Robert Jenssen: robert.jenssen@uit.no
Professor Michael Kampffmeyer: michael.c.kampffmeyer@uit.no
Associate Prof. Elisabeth Wetzer elisabeth.wetzer@uit.no
Associate Prof. Kristoffer Wickstrøm kristoffer.k.wickstrom@uit.no
Head of Department of Physics and Technology, Professor Olav Gaute Hellesø: olav.gaute.helleso@uit.no
You must hold a PhD in machine learning or a related relevant field and you must document experience in executing independent original research.
You must have a strong background in machine learning methodology research with focus on developing novel methodology in deep learning (neural networks), probabilistic learning, geometric learning, knowledge-driven learning, information theoretic learning, or combinations thereof. Such qualifications must be documented by publications at a high level within machine learning journals and conferences such as IEEE TPAMI, IEEE NNLS, IJCAI, AAAI, ICML, NeurIPS, ICLR, CVPR, ECCV, ICCV, UAI, etc. Competence and experience with relevant applications, particularly in the health domain, will be emphasized, as well as interdisciplinary work. We are looking for a blend of research on generic methodology development and research towards specific applications.
You must be fluent in oral and written English and should have a good command of Norwegian or a Scandinavian language. Applicants who are not fluent in a Scandinavian language must be willing to learn Norwegian within 3 years and pass the language exam level B2 (“Bergenstesten” or equivalent).
UiT offers relevant Norwegian language courses for new employees.
We will evaluate contributions to cutting edge machine learning methodology, towards applications and inter-disciplinary work. At UiT we put emphasis on the quality, relevance and significance of the research work, in accordance with the principles of The San Francisco Declaration on Research Assessment (DORA). The publishing record will be assessed with respect to the career stage of the candidate, and we will emphasize the potential of the candidates more than the seniority. Teaching experience and your teaching philosophy and strategy will also be part of the evaluation. Documented external funding, experience with research leadership and relevant collaboration with industry for innovation activities will be rated positively for the Associate Professor position and will be an important aspect for the Full Professor position.
We will emphasize the applicant’s motivation for the position and personal suitability, including collaboration skills and approach to make a good work environment. UiT wishes to increase the proportion of female researchers in academic positions. In cases where two or more applicants are found to be approximately equally qualified, female applicants will be given priority.
Qualification requirements for the position as Associate Professor:
All applicants for teaching and research positions shall document their pedagogical competence. Those who do not satisfy the requirements may be appointed on a permanent basis on the condition that they satisfy the requirements within two years of appointment.
Qualification requirements for the position as Professor:
In addition you must document:
To be awarded a professorship, you must document substantially more extensive research of high quality than that required to be awarded a doctorate degree. You must document academic activity at a high level over the previous six years, and that this points forwards towards continued activity at professorial level.
UiT follows national guidelines for professorial promotion within Mathematics, Science and Technology disciplines when evaluating candidates for professorships.
All applicants for teaching and research positions shall document their pedagogical competence.
You must have acquired basic competence for teaching and supervision at higher education level. This includes basic skills in planning, conducting, evaluating and developing teaching and guidance.
Documentation requirement
a) Applicants who have completed education or courses designed to provide teaching competence for teaching at universities and colleges, equivalent to a minimum of 200 hours, must attach diploma and curriculum for the completed course.
b) Other applicants shall describe, assess and document their competence as a teacher and supervisor. The skills must be documented in the form of a teaching portfolio.
For professor positions, experience with teaching and supervision in higher education corresponding to three years in a full-time position is required.
Applicants for professor positions shall also document that the supplementary criteria are satisfied:
If the pedagogical competence can be acquired within two years of appointment, applicants shall not be ranked based on pedagogical competence.
Those who do not satisfy the requirements may be appointed on a permanent basis on the condition that they satisfy the requirements within two years of appointment.
For information about basic pedagogical competence and teaching portfolio, see: https://result.uit.no/om-pedagogisk-mappe/ (Only in Norwegian)
The remuneration for Associate Professor is in accordance with code 1011. A compulsory contribution of 2 % to the Norwegian Public Service Pension Fund is deducted. In addition, UiT pays approx. 12 % directly to the Pension Fund on top of the salary.
Employees in permanent positions as professor/associate professor have the right to apply for a paid sabbatical (research and development).
In general, a professor/associate professor spend an equal amount of time on teaching and research and development work, after time spent on other duties has been deducted. As a norm, the time resources spent on administrative duties constitutes 5 % for academic staff in this category of position. The allocation of working hours is flexible and allocated on a case-by-case basis.
More information about moving to Tromsø: http://uit.no/mobility.
We make the appointment in accordance with the regulations in force concerning State Employees and Civil Servants, and guidelines at UiT. At our website, you will find more information for applicants.
Personal data given in an application or CV is processed in accordance with the Personal Data Act. You may request not to be registered on the public list of applicants, but the University may decide that your name will be made public. You will receive advance notification in the event of such publication.
If you have to relocate to Tromsø then the Faculty 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.
The successful candidate must be willing to get involved in the ongoing development of their department and the university as a whole.
The allocation of working hours is flexible and allocated on a case-by-case basis. In general, Professor/Associate Professors will spend an equal amount of time on teaching and research and development work. As a norm, the time resources spent on administrative duties constitutes 5 % for academic staff.
The remuneration for Professor is in accordance with the State salary scale code 1013. The remuneration for Associate Professor is in accordance with the State salary scale code 1011.
As a state employee, you have one of the best pension schemes availiable. For more information see: spk.no.
UiT The Arctic University in Norway is working actively to promote equality, gender balance and diversity among employees and students, and to create an inclusive and safe working environment. In the event that two or more applicants are found to be approximately equally qualified, female applicants will be given priority.
We believe that inclusion and diversity is 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 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.
The application must include:
Documentation must be in English or a Scandinavian language. Submit applications electronically through Jobbnorge.
The applicants will be assessed by an expert committee. The committee's mandate is to undertake an assessment of the applicants' qualifications on the basis of the written material presented by the applicants, and the detailde description draw up for the position.
The applicants who are assessed as best qualified will be called to an interview. The interview shall among other things, aim to clarify the applicants personal suitability for the position and motivations. A trial lecture may also be held.
The appointment is made in accordance with State regulations and guidelines at UiT. At our website, you will find more information 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.
More information about moving to Norway and working at UiT: http://uit.no/mobility
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.
In case of discrepancies between the Norwegian and the English version of this description, the Norwegian version takes precedence.
Om bedriften
Tittel
Associate Professor/Professor in Machine Learning
Oppstart
Type engasjement
Fast
Sektor
Offentlig
Omfang
Heltid
Antall stillinger
1
Del annonsen
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Om stillingen
The Department of Physics and Technology has up to three open permanent positions as Associate Professor and/or Professor. Early career scientists, with a promising CV, as well as experienced candidates are invited to apply, respectively for Associate and full Professor.
The faculty members will join the UiT Machine Learning Group. The group is internationally recognized, with research ranging from foundational machine learning methodology and algorithms to applied AI development. The range of applications is wide, with a particular focus on healthcare. The new faculty members shall further strengthen the scientific excellence and high-profile of the group, notably in the Centre of Research-based Innovation SFI Visual Intelligence, which is headed by the group, and the Centre of Excellence SFF Integreat – The Norwegian Centre for Knowledge-based Machine Learning.
The workplace is at UiT in Tromsø. You must be able to start in the position in Tromsø within 6 months after receiving the offer.
You have a strong desire to develop the next generation machine learning methodologies. You find motivation by extracting knowledge from ever-increasing and challenging data, such as images, time series, tabular data, or other sources. You understand the importance of gaining insight, creating value, and solve real world applications of value to humankind and towards the UN sustainability goals. You find joy in teaching and you hold high ethical standards of your research, teaching and innovations.
Your interests are in neural networks research, where key research challenges are learning from limited data, interpretability and XAI, uncertainty quantification, and the integration of prior knowledge and context, or in general within self-supervised learning, unsupervised learning, representation learning, generative AI, graph-based learning, information theoretic learning, and/or neural knowledge-based learning. The Machine Learning Group has an internationally recognized expertise in developing theoretical and conceptual aspects of machine learning. This is strengthened by the recent centre of excellence SFF Integreat, where the group plays a major role.
Within the UiT Machine Learning Group and the SFI Visual Intelligence centre, the main applications are within health and medicine. Our research contributes to diagnosis and decision support by extracting patient-specific information from electronic health records and through medical computer vision for important clinical tasks such as cancer characterization. You can help transform healthcare for future needs, with AI as an integral part. Other relevant application areas include marine sciences for abundance estimation and sustainable harvest of the oceans, as well as environmental monitoring. Through machine learning, we can aid the climate, the oceans and Earth.
As a faculty member in the UiT Machine Learning Group, you will have the chance to make an impact on the world and to help shape the future of society with better machine learning solutions that are trustworthy and ethically sound. You are expected to collaborate with the current members in the group. The UiT Machine Learning Group relies strongly on teamwork and joint supervision of students. If you are applying for the Full Professor position, you are expected to bring your network of national and international collaborations and engage them in new connections with the group members.
Further information about the position and UiT is available by contacting:
Head of Machine Learning Group, Associate Professor Benjamin Ricaud; benjamin.ricaud@uit.no
Director of Visual Intelligence and Co-Director of Integreat, Professor Robert Jenssen: robert.jenssen@uit.no
Professor Michael Kampffmeyer: michael.c.kampffmeyer@uit.no
Associate Prof. Elisabeth Wetzer elisabeth.wetzer@uit.no
Associate Prof. Kristoffer Wickstrøm kristoffer.k.wickstrom@uit.no
Head of Department of Physics and Technology, Professor Olav Gaute Hellesø: olav.gaute.helleso@uit.no
You must hold a PhD in machine learning or a related relevant field and you must document experience in executing independent original research.
You must have a strong background in machine learning methodology research with focus on developing novel methodology in deep learning (neural networks), probabilistic learning, geometric learning, knowledge-driven learning, information theoretic learning, or combinations thereof. Such qualifications must be documented by publications at a high level within machine learning journals and conferences such as IEEE TPAMI, IEEE NNLS, IJCAI, AAAI, ICML, NeurIPS, ICLR, CVPR, ECCV, ICCV, UAI, etc. Competence and experience with relevant applications, particularly in the health domain, will be emphasized, as well as interdisciplinary work. We are looking for a blend of research on generic methodology development and research towards specific applications.
You must be fluent in oral and written English and should have a good command of Norwegian or a Scandinavian language. Applicants who are not fluent in a Scandinavian language must be willing to learn Norwegian within 3 years and pass the language exam level B2 (“Bergenstesten” or equivalent).
UiT offers relevant Norwegian language courses for new employees.
We will evaluate contributions to cutting edge machine learning methodology, towards applications and inter-disciplinary work. At UiT we put emphasis on the quality, relevance and significance of the research work, in accordance with the principles of The San Francisco Declaration on Research Assessment (DORA). The publishing record will be assessed with respect to the career stage of the candidate, and we will emphasize the potential of the candidates more than the seniority. Teaching experience and your teaching philosophy and strategy will also be part of the evaluation. Documented external funding, experience with research leadership and relevant collaboration with industry for innovation activities will be rated positively for the Associate Professor position and will be an important aspect for the Full Professor position.
We will emphasize the applicant’s motivation for the position and personal suitability, including collaboration skills and approach to make a good work environment. UiT wishes to increase the proportion of female researchers in academic positions. In cases where two or more applicants are found to be approximately equally qualified, female applicants will be given priority.
Qualification requirements for the position as Associate Professor:
All applicants for teaching and research positions shall document their pedagogical competence. Those who do not satisfy the requirements may be appointed on a permanent basis on the condition that they satisfy the requirements within two years of appointment.
Qualification requirements for the position as Professor:
In addition you must document:
To be awarded a professorship, you must document substantially more extensive research of high quality than that required to be awarded a doctorate degree. You must document academic activity at a high level over the previous six years, and that this points forwards towards continued activity at professorial level.
UiT follows national guidelines for professorial promotion within Mathematics, Science and Technology disciplines when evaluating candidates for professorships.
All applicants for teaching and research positions shall document their pedagogical competence.
You must have acquired basic competence for teaching and supervision at higher education level. This includes basic skills in planning, conducting, evaluating and developing teaching and guidance.
Documentation requirement
a) Applicants who have completed education or courses designed to provide teaching competence for teaching at universities and colleges, equivalent to a minimum of 200 hours, must attach diploma and curriculum for the completed course.
b) Other applicants shall describe, assess and document their competence as a teacher and supervisor. The skills must be documented in the form of a teaching portfolio.
For professor positions, experience with teaching and supervision in higher education corresponding to three years in a full-time position is required.
Applicants for professor positions shall also document that the supplementary criteria are satisfied:
If the pedagogical competence can be acquired within two years of appointment, applicants shall not be ranked based on pedagogical competence.
Those who do not satisfy the requirements may be appointed on a permanent basis on the condition that they satisfy the requirements within two years of appointment.
For information about basic pedagogical competence and teaching portfolio, see: https://result.uit.no/om-pedagogisk-mappe/ (Only in Norwegian)
The remuneration for Associate Professor is in accordance with code 1011. A compulsory contribution of 2 % to the Norwegian Public Service Pension Fund is deducted. In addition, UiT pays approx. 12 % directly to the Pension Fund on top of the salary.
Employees in permanent positions as professor/associate professor have the right to apply for a paid sabbatical (research and development).
In general, a professor/associate professor spend an equal amount of time on teaching and research and development work, after time spent on other duties has been deducted. As a norm, the time resources spent on administrative duties constitutes 5 % for academic staff in this category of position. The allocation of working hours is flexible and allocated on a case-by-case basis.
More information about moving to Tromsø: http://uit.no/mobility.
We make the appointment in accordance with the regulations in force concerning State Employees and Civil Servants, and guidelines at UiT. At our website, you will find more information for applicants.
Personal data given in an application or CV is processed in accordance with the Personal Data Act. You may request not to be registered on the public list of applicants, but the University may decide that your name will be made public. You will receive advance notification in the event of such publication.
If you have to relocate to Tromsø then the Faculty 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.
The successful candidate must be willing to get involved in the ongoing development of their department and the university as a whole.
The allocation of working hours is flexible and allocated on a case-by-case basis. In general, Professor/Associate Professors will spend an equal amount of time on teaching and research and development work. As a norm, the time resources spent on administrative duties constitutes 5 % for academic staff.
The remuneration for Professor is in accordance with the State salary scale code 1013. The remuneration for Associate Professor is in accordance with the State salary scale code 1011.
As a state employee, you have one of the best pension schemes availiable. For more information see: spk.no.
UiT The Arctic University in Norway is working actively to promote equality, gender balance and diversity among employees and students, and to create an inclusive and safe working environment. In the event that two or more applicants are found to be approximately equally qualified, female applicants will be given priority.
We believe that inclusion and diversity is 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 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.
The application must include:
Documentation must be in English or a Scandinavian language. Submit applications electronically through Jobbnorge.
The applicants will be assessed by an expert committee. The committee's mandate is to undertake an assessment of the applicants' qualifications on the basis of the written material presented by the applicants, and the detailde description draw up for the position.
The applicants who are assessed as best qualified will be called to an interview. The interview shall among other things, aim to clarify the applicants personal suitability for the position and motivations. A trial lecture may also be held.
The appointment is made in accordance with State regulations and guidelines at UiT. At our website, you will find more information 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.
More information about moving to Norway and working at UiT: http://uit.no/mobility
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.
In case of discrepancies between the Norwegian and the English version of this description, the Norwegian version takes precedence.
Relaterte stillinger
Om bedriften