Associate Professor in Computerized Image Analysis and Machine Learning
The deadline for applying to this position has passed.
Uppsala University is a comprehensive research-intensive university with a strong international standing. Our mission is to pursue top-quality research and education and to interact constructively with society. Our most important assets are all the individuals whose curiosity and dedication make Uppsala University one of Sweden’s most exciting workplaces. Uppsala University has 46.000 students, 7.300 employees and a turnover of SEK 7.3 billion.
The Department of Information Technology has approximately 300 employees and 4600 students and conducts research and education in a spectrum of areas within Computer Science and Information Technology. The research is organised in five Divisions, and the research at the Division of Visual Information and Interaction is a unique combination of expertise in computerised image analysis and human-computer interaction. The image analysis and machine learning research within Vi2 is focused towards theoretical analysis and algorithm development and applications within primarily biomedicine and handwritten text recognition. More information about the department and its activities can be found at www.it.uu.se.
Description of subject area of the employment: Computerised image analysis and processing encompass the development and analysis of theory and methods to create and handle digital images and extract information from the image content. The methods aim at one or more of the following: to quantitatively or qualitatively describe the content of an image, to segment/divide and image into meaningful parts in order for these to be automatically identified, described or interpreted, to develop autonomous and interactive methods and systems for image capturing, analysis and visualisation, to visualise a data subset for interpretation and analysis, to compress/represent an image for efficient transfer and storage. The methods are often based on machine learning why the position has a large machine learning component.
- Teaching, research and administration. Teaching duties include course responsibility and course administration and supervision of second- and third-cycle students. A lot of the teaching will be part of the newly established Master program in Image Analysis and Machine Learning. Development of and teaching on new courses (including contract courses/teaching) within the subject area may a part of the duties as well as supervision, subject reviewing, and examination of thesis projects.
- Follow developments within the subject area and the development of society in general that is important for the work at the university.
- The position may include management/steering-board and administrative appointments or tasks within the division, institution and faculty, such as director of studies, research arena coordinator, equal opportunity representative/coordinator or collaboration representative/coordinator, local administration of the division's web pages, publications reporting, seminar series etc.
- PhD in the subject area or have the corresponding research competence or some other professional expertise.
- Research Expertise and Teaching Expertise. It is necessary that the pedagogical skills, the research expertise and the professional skills are relevant to the content of the employment and the tasks that will be included in the employment.
- Applicants must have completed teacher training of relevance to operations at the University, comprising ten weeks, or have acquired the equivalent knowledge. If special circumstances apply, this training for teachers in higher education may be completed during the first two years of employment.
- Documented ability to teach in Swedish and English is a requirement unless special reasons prevail. The holder is expected to be able to teach in Swedish within two years.
- Personal capabilities necessary to carry out fully the duties of the appointment.
Assessment Criteria/Ranking of applicants that fulfil the above-mentioned qualifications required
The ranking of eligible applicants will be based primarily on research and teaching expertise, which will be given equal weight.
Research Expertise comprises research merits. In addition to academic merits, research merits from other activities, including technology development, may also be taken into account including research merits obtained outside the academy, which includes for example technology development and innovation ability. In assessing research expertise research quality must be the prime consideration. The scope of research, primarily in regard to depth and breadth, must also be afforded consideration. In assessing research expertise special weight will be attached to research merits in theoretical image analysis and machine/deep learning and cross-disciplinary applications of these subjects.
Furthermore, consideration must be given to the capacity to plan, initiate, lead, and develop research and education in the third cycle, the ability to acquire funding for research in competition, as well as the demonstrated capacity to interact with others both within academia and in the wider community.
Teaching Expertise comprises educational and teaching qualifications. This expertise can have been achieved outside the academy through supervision, internal training, mentoring programs, etc. In assessing teaching expertise teaching quality must be the prime consideration. The scope of teaching experience, in terms of both breadth and depth, must also be afforded consideration. In assessing teaching expertise special weight will be attached to merits in merits in subject specific teaching (image analysis and machine learning in image analysis).
Furthermore, consideration must be given to the capacity to plan, initiate, lead, and develop teaching and instruction, as well as the ability to connect research to teaching in respect to research in the subject at hand, subject didactics, as well as teaching and learning in higher education. The ability to interact concerning issues of teaching and learning in higher education with actors inside and outside the University is also included in teaching expertise.
Administrative Expertise is important for the employment and will be afforded consideration. Administrative expertise is demonstrated, for example, through the capacity to plan, organise, and prioritise work in an efficient and task-related manner as well as through the ability to assign and observe time frames. Expertise includes overall operational planning and the capacity to manage resources in a way that reflects operational priorities as well as the ability to work in a structured manner based on an awareness of goals and quality. Administrative expertise also includes entrepreneurship.
Management Expertise is important and will be afforded consideration. Management expertise is demonstrated through the capacity to lead operations and personnel, make decisions, take responsibility, and motivate others, providing them with what is needed for the efficient achievement of common goals. The abilities to coordinate the group and help create a sense of involvement, participation, and enjoyment in work and to deal with conflicts constitute further examples of demonstrated expertise.
Collaboration Expertise is important and will be afforded consideration. Collaborative expertise is demonstrated by the ability and skill of planning, organising and implementing interaction with the surrounding community. Popular publications, public debate and lectures are examples of forms of interaction with the surrounding community. Other examples of collaboration are patent applications, commercialisation and industrial cooperation. The ability to translate knowledge sharing with the surrounding community into activities of importance to theeducation's development and quality is part of the collaboration expertise.
All merits must be documented in a manner that makes it possible to assess both quality and scope.
In filling this position the university aims to appoint the applicant who, following a qualitative holistic assessment of her/his competence and expertise, is judged to have the best potential to carry out and develop the relevant duties and to help advance operations.
An applicant who is offered an employment as Associate Professor can be promoted to Professor if he/she has applied for this, is qualified for such a post, and moreover has been deemed suitable on the basis of the specific criteria established by the faculty board.
In an overall assessment of the applicant’s qualifications, parental leave, part-time work relating to care of children, union assignments, military service, or the like are to be regarded as work experience.
Salary: Individually negotiated salary.
Starting date: As soon as possible or as otherwise agreed
Type of employment: Permanent full-time position.
Scope of employment: 100 %
For further information about the position please contact: Head of Division, Professor Robin Strand, +46 (0)70 3442224, email@example.com.
Please submit your application by September 25 2020, UFV-PA 2020/2505.
In the event of any disagreement between the English and the Swedish versions of this announcement, the Swedish version takes precedence.
If you are an international candidate, you will find a lot of information about working and living in Sweden at www.uu.se/joinus.
Please do not send offers of recruitment or advertising services.
Submit your application through Uppsala University's recruitment system.
Placement: Department of Information Technology
Type of employment: Full time , Permanent position
Pay: Fixed salary
Number of positions: 1
Working hours: 100%
County: Uppsala län
Number of reference: UFV-PA 2020/2505
Last application date: 2020-09-25
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