Welcome to Linnaeus University! Here you'll meet 2 200 staff members and 40 000 students, all united in following the vision to set knowledge in motion for a sustainable societal development. With us, research and education are conducted with an eye towards the future. Our proximity to the business world, both locally and globally, gives us a wide reach and the ability to create change that makes an impact. All that's needed is a place where ideas have the space to meet and grow. That's what we've created – and you are invited.

Change starts here!

The Faculty of Technology is one of five faculties at Linnaeus University. We bring together the university's education and research in technical subjects. Our operations are organised into nine departments and a faculty office. We also house the Linnaeus University Centre DISA and two Linnaeus Knowledge Environments: Green Sustainable Development and Digital Transformations. Several of the faculty's research groups collaborate within the strategic research area of Forest Values.

The Department of Computer Science and Media Technology is responsible for many educational programs at basic and advanced levels within computer science, software development, and media technology. Currently, more than 60 staff members work in the department. The department has a strong connection with other departments of Linnaeus University.

Subject area for the position: Computer and information science
Location: Växjö. Since Linnaeus University is located in both Växjö and Kalmar, travel between the two may be required.

Terms and hours: The doctoral studentship is limited in time in accordance with the Higher Education Ordinance. The studentship is full-time.
Start date: Starting date as agreed upon.

Job description

The information visualization research group (ISOVIS, https://cs.lnu.se/isovis) at Linnaeus University is looking for a PhD candidate to engage in research related to Visual Analytics and Information Visualization. The candidate will work across a variety of topics including, but not limited to, Machine Learning, Explainable AI, Network Visualization, Graph Drawing, and Dimensionality Reduction. Through our collaborative environment with experts in these topics, the candidate will have the opportunity to work into one or more of these subjects, contributing to the advancement of knowledge in their respective fields. Join us in our pursuit of academic excellence and innovation as we shape the future of technology and research.

The Higher Education Ordinance states that a person who is employed, as a PhD student should primarily devote himself/herself to his/her own studies. However, an employee may to a limited extent work with education, research and administration. Such work may, before the doctoral degree has completed, not cover more than 20% of a full-time work.

Eligibility

A person meets the general entry requirements for third-cycle studies if they:

• Have been awarded a degree at the second-cycle level,




• Have at least 240 credits of passed courses, of which at least 60 credits are at the second-cycle level; or




• Have acquired essentially equivalent knowledge in some other way, in or outside Sweden.

Specific prerequisites for admission to graduate studies in Computer and Information Science are required:

• approved courses of a minimum of 90 credits in the subject Computer and Information Science or the equivalent, and




• an individual study project of a minimum of 15 credits in the subject Computer and Information Science, or the equivalent.

Other requirements

• Independence and ability to solve challenging problems.




• Excellent work ethic and commitment to the job.




• Excellent English skills, both written and verbal.

Desirable qualifications

Good Swedish skills are a merit, but not mandatory. It is of great advantage if the applicant has work experience or a thesis on Information Visualization and/or Artificial Intelligence. Excellence in previous work and a good publication track record is desirable.

Very good programming skills (e.g., JavaScript and D3.js, Python, WebGL/OpenGL, Scikit-learn, PyTorch, TensorFlow, and Keras), experience in developing web-based visualization tools, and solid training in data mining or machine learning are highly preferred.

We attach great importance to personal suitability. Emphasis will be put on good ability for structured work, good initiative, ability to make priorities, accuracy and service minded, ability to run and complete tasks within given time frames, flexibility and very good collaboration skills. 

Assessment criteria

Applications to graduate studies are governed by rules in the admission regulations.

The selection of candidates is made with regard to the applicant’s ability to successfully complete and benefit from their studies at the graduate level. The assessment takes into account academic skills documented in scientific works, especially focused on the quality of the essays at the undergraduate level, any advanced work and other scientific or scholarly works. The assessment also takes into account breadth and composition of the undergraduate degree as well as the picture which the intended principal academic supervisor, examiner, and other colleagues in the research group and the subject obtained of the applicant’s potential.

The applicants are ranked by a review group appointed by the subject.  

Contact

Head of department Morgan Ericsson, morgan.ericsson@lnu.se. 

Assistant supervisor (Member of ISOVIS) Claudio Linhares, claudio.linhares@lnu.se.

HR partner Erika Hjelmer, erika.hjelmer@lnu.se

Last day for application is 2024-08-15

Linnaeus University has the ambition to utilize the qualities that an even gender distribution and diversity brings to the organization.

Please apply by clicking on the Apply button at the bottom of the ad. Applicants are requested to the application resolving CV, cover letter , a copy of a relevant essay , grades and certificates and other relevant documents. The applicant also requested to submit with their application a proposed research plan within the current area of research. All documents must be attached to digital in the application. The application and other documents shall be marked with the reference number. All documents cited must be received by the University no later than 23.59 (Local time in Sweden) on the closing day.