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Description
The Faculty of Health, Science and Technology invites applications for a doctoral studentship in Computer Science at the Department of Mathematics and Computer Science.
As a doctoral student you will contribute to important knowledge for society and be part of the university’s significant investment in research education, for this position in the area of Artificial Intelligence.
The successful candidate is expected to conduct research in the broad field of Artificial Intelligence (AI). Specifically, in the robustness, reliability and scalability aspects of Al algorithms (Deep Learning and Reinforcement Learning). She/he is expected to learn and employ the latest Al tools and methodologies, e.g., generative Al, to solve these problems. She/he has the opportunity to test the developed ideas within the framework of 5G/6G networks and distributed computational systems. To facilitate this, here, at Karlstad University, we have the state-of-the-art 5G testbed, and multiple distributed computing testbeds. The candidate will have an opportunity to contribute to these testbeds through Al benchmarks.
The work will be carried out in close collaboration with other researchers in the Distributed Intelligent Systems and Communications (DISCO) group at the Department of Mathematics and Computer Science. DISCO is a leading, internationally renowned research unit in the field of mobile communication systems and services. Multiple research projects funded by European and national research organisations have created a highly innovative team of experts, with excellent research networks and working conditions for independent scientific work.
Research within the DISCO group is based on a project-centered and collaborative culture. Applicants for the offered position are expected to contribute to this research environment in an open and collaborative way, as well as collaborate with our partners outside Computer Science, e.g., industrial partners, in the context of interdisciplinary projects.
Duties
As a doctoral student, you will primarily dedicate time to your own studies. The doctoral programme, comprising 240 credits for a Degree of Doctor, is an opportunity to study while being paid a salary in combination with work and provides a stepping stone for a career in academia. The doctoral student is expected to work independently and be prepared to contribute to the activities and development of the subject and the department. Teaching and administrative duties may also be included upon agreement (maximum 20% of full time). Work as a doctoral student allows for great freedom and flexibility in terms of how you structure your day. It takes commitment, discipline and a structured approach in order to successfully complete a doctoral thesis. Experienced supervisors offer guidance and support along the way. To contribute to a positive work environment and further the department’s activities, we expect you to be a present and active part of the day-to-day operations and workplace community.
Qualification requirements
To be eligible for a doctoral studentship, the applicant must meet the general and specific entry requirements (Higher Education Ordinance, Chap. 7, Sect. 35).
To meet the general entry requirements, the applicant must have been awarded a second-cycle qualification, satisfied the requirements for courses comprising at least 240 credits of which at least 60 credits were awarded in the second- cycle, or acquired substantially equivalent knowledge in some other way in Sweden or abroad (Higher Education Ordinance, Chap. 7, Sect. 39).
To meet the specific entry requirements for third-cycle studies in Computer Science, the applicant must have completed a Master’s degree (60 credits) in Computer Science, a Master’s degree (120 credits) in Computer Science or a Master of Science degree in Computer Engineering. A person who, in some other way, in the country or abroad, has acquired equivalent qualifications also meets the specific entry requirements.
Admission and assessment criteria
To be eligible for doctoral studies, the applicant must be considered to have the ability required to benefit from the programme (Higher Education Ordinance, Chap. 7, Sect. 35). Admission is based on individual assessment.
The assessment will focus on the applicant’s performance in previous studies and the quality of any independent projects completed during these studies. The most important assessment criteria for the selection are scientific skills, language skills in English, and suitability for research in core Artificial Intelligence.
Special weight will be given to knowledge of both theory and algorithm development within the field of Artificial Intelligence. In particular, special weight will be given to the analytic skills and the skills surrounding algorithm development within Deep Learning, Reinforcement Learning, and Sequential Decision Making.
Considerable weight will also be given to personal qualities such as the ability to cooperate, sound judgement, taking responsibility, commitment and a positive attitude towards colleagues and students, and the intention to be a present and active part of the research environment.
Terms
Upon admission to doctoral studies, the person will be offered the appointment of doctoral student (Higher Education Ordinance, Chap. 5, Sect. 3). The position comprises four years of full-time studies, or five years at a study rate of 80% with 20% teaching or other departmental duties. The position is fixed-term- one year initially, followed by possible extensions by a maximum of two years at a time. Start date by agreement.
The salary for the doctoral studentship corresponds to the standard level of salary for doctoral students and progresses in accordance with a local collective agreement.
Application
Submit the application via the University’s web-based recruitment tool, Varbi.
Applicants are responsible for submitting a complete application in accordance with the advertisement, for providing translations of any documents written in a language other than Swedish, Norwegian, Danish or English, and for ensuring that the documentation allows for objective and qualitative assessments. A complete application should be submitted by the application deadline. An incomplete application may jeopardise a fair assessment of qualifications. The application should include:
- a cover letter where the applicant describes her or himself, details the reasons behind their interest and the qualifications for the position,
- a list of qualifications (CV),
- degree certificate with a complete transcript of the courses included, or a certified list of completed courses with grades and dates,
- copy of Master’s thesis or equivalent,
- where applicable, copies of publications or certificates for other qualifications,
- any letters of recommendation,
- two references, such as a teacher, supervisor, or previous or current superior.
Attach all the documents and publications you wish to be considered to the electronic application (do not just provide links). Name each uploaded document to clearly indicate its content.
Documents that cannot be submitted electronically should be sent to the following address:
Karlstads universitet
Hanna Ljungdahl
651 88 KARLSTAD
Application deadline: 24-04-15
State the reference number: REK 2024/41.
Applicants with qualifications from abroad
If you have qualifications from a university outside Sweden or if they have not been recognised by a Swedish authority before, it is important that you attach degree certificates and official transcripts to facilitate the recognition of foreign qualifications.
Provide a contact for the degree-awarding institution (phone number or email) who can verify your qualifications.
We look forward to your application!
Karlstad University has chosen advertising channels for this recruitment and firmly declines any contact with advertising or recruitment agencies.
HR Excellence in Research
Karlstad University received the European Commission’s HR Excellence in Research award September 2020. The award is issued to employers with a stimulating work environment and good conditions for researchers and its continuous improvement. The award also conveys the university’s commitment to fair and transparent recruitment as well as favorable professional development for researchers. Read more: kau.se/hrs4r
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