Assistant Professor in Computing Science with a focus on knowledge-based AI methods
1 month ago
Background
The department is home to a broad range of research and competence in different areas of Artificial Intelligence research. Logic- and knowledge-based methods, techniques and their practical realization are fundamental for many of them. Thus, we now plan to strengthen our competence in knowledge-based AI and in this way, also create stronger collaboration opportunities between different research areas at the department.
The position is financed by and comes with a substantial recruitment package from the Wallenberg AI, Autonomous Systems and Software Program (WASP). The package includes funding for two PhD students (four years each) and two post docs (two years each) in addition to running costs.
Wallenberg AI, Autonomous Systems and Software Program (WASP) is Sweden’s largest individual research program ever, a major national initiative for strategically motivated basic research, education and faculty recruitment. The program addresses research on artificial intelligence and autonomous systems acting in collaboration with humans, adapting to their environment through sensors, information and knowledge, and forming intelligent systems-of-systems.
The vision of WASP is excellent research and competence in artificial intelligence, autonomous systems and software for the benefit of Swedish industry.
Read more: .
Duties
Your duties as Assistant Professor mainly include research and teaching, but may also include tasks in administration, academic leadership, and industry collaboration. For the first 5 years, you are guaranteed 80% research time and 20% for teaching and administration; year six will be 75% research and 25% teaching and administration. After this 6-year period, and given a successful promotion, the distribution between research and teaching may change over time depending on needs and available resources.
Your research will be in the area logic and reasoning in AI. We expect your research to focus on logic-based reasoning systems, argumentation, ontologies, reasoning under uncertainty, and rational agents.
We encourage collaboration with industry and society. We expect that the successful candidate will develop synergies between different research groups at the department, in particular in the area of AI.
In teaching, you will mostly develop and give courses in the area logic and reasoning, together with other teachers. You may also supervise thesis work. Teaching in courses on basic level may also occur.
Eligibility requirements
According to Chapter 4, Section 4 of the Higher Education Ordinance: A person qualified for appointment as an Assistant professor is a person who has been awarded a PhD or has the corresponding research expertise. Primary consideration should be given to a person who has been awarded a PhD or achieved the equivalent expertise within five years prior to the deadline for application for employment as an Assistant professor. However, a person who has been awarded a PhD or achieved the equivalent expertise at an earlier date may also be considered if there are exceptional circumstances. Exceptional circumstances are sick leave, parental leave or other similar circumstances.
Assessment criteria
The assessment criteria for appointment as an Assistant professor shall be the degree of such expertise required as a qualification for employment.
Thereafter the degree of pedagogical expertise as well as administrative and other experience of significance with regard to the employment’s research field and the employment tasks that may be included in the position.
Scientific expertise
Scientific expertise shall be demonstrated through independent scientific productivity. The criteria for assessment are:
Breadth and depth of research – quality and extent Originality in research Productivity Contributions to the international research community Commissions of trust within the research community Ability to competitively obtain research funding Collaboration with the surrounding communityResearch needs to be in the area of logic and reasoning in Artificial Intelligence.
Pedagogical expertise
The criteria for evaluation of pedagogical expertise are:
ability to plan, implement and evaluate teaching and an ability to supervise and examine students at every level of education ability to vary teaching methods and examination forms in relation to anticipated study results and the nature of the subject experience of collaboration with the surrounding society in planning and implementation of education participation in the development of learning environments, teaching aids and study resources a reflective approach to student learning and one’s own role as a teacherPedagogical expertise can be attained through education in university pedagogy, other education of relevance for teaching at a university level or documented and proven experience teaching at the university level.
Experience in teaching in the areas of logic and reasoning is a merit.
Other assessment criteria
A general basis for assessment for all teaching categories is both good cooperative skills and the expertise and suitability in general required to complete the work duties satisfactorily.
The criteria for evaluation of administrative expertise are:
Participation in working groups or committees (department, faculty or university level) Experiences of collaboration outside the academy Experience of organizing research and educational activities Experience in collaboration with industry is a merit.
Assessment criteria and their weight
In the selection of candidates, the degree of research expertise shall be decisive. In addition, the degree of educational expertise as well as administrative and other competences of importance shall be taken into account with regard to the subject content of the employment and the duties to be included in the employment.
Further details
As an employee at Umeå University, you're offered a wide variety of benefits that promote a good work- life balance, read more about benefits here.
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