Post-doctoral fellow in cartographic visualization and machine learning - Hiring in process/Finished, not possible to apply

Subject description

This postdoctoral position is focused on visualization of geographic data, especially in automated map labelling. The subject of the position is geographic information science linked to computer science with elements of machine learning and artificial intelligence (AI).

Work duties

The main task is to conduct research in automated labeling of maps. The research approach is data driven where we utilize maps that have been interactively created by experienced cartographers. Through a collaboration with a cartographic company, we have access to hundreds of thousands of maps with high-quality cartography (see https://www.citywayfinding.com/), where substantial manual text editing has been performed. These maps can be used to improve current (semi-) automated labeling methods, which are estimated to fulfill around half of the requirements for high-quality cartography. To achieve this machine learning / AI methods will be applied.

The work includes running a research project together with the principal investigator and collaborating with partners in academia and in companies. Applying for external research funding can be included.

The position also includes teaching at the undergraduate level and/or advanced level and/or supervision of master thesis. Teaching is at most 20% of the working time. If necessary, the opportunity is given for three weeks of higher education pedagogical training.

Qualification requirements

Appointment to a post-doctoral position requires that the applicant has a PhD, or an international degree deemed equivalent to a PhD, within geographic information science, computer science, applied mathematics (or equivalent), completed no more than three years before the last date for application. Under special circumstances, the doctoral degree can have been completed earlier.

Additional requirements:

• Very good oral and written proficiency in English.
• Very good programming skills.

Assessment criteria and other qualifications

This is a career development position primarily focused on research. The position is intended as an initial step in a career, and the assessment of the applicants will primarily be based on their research qualifications and potential as researchers.

Particular emphasis will be placed on research skills within the subject.

For appointments to a post-doctoral position, the following shall form the assessment criteria:

• A good ability to develop and conduct high quality research.
• Teaching skills.

Additional assessment criteria:

• Knowledge in cartography and visualization of geographical data.
• Experience in machine learning and AI.
• Oral and written proficiency in Swedish.

Consideration will also be given to good collaborative skills, drive and independence, and how the applicant’s experience and skills complement and strengthen ongoing research within the department, and how they stand to contribute to its future development.

Terms of employment

This is a full-time, fixed-term employment of a maximum of 2 years. The period of employment is determined in accordance with the agreement “Avtal om tidsbegränsad anställning som postdoktor” (“Agreement on fixed-term employment as a post-doctoral fellow”) between Lund University, SACO-S, OFR/S and SEKO, dated 4 September 2008.

Instructions on how to apply

Applications shall be written in English and be compiled into a PDF-file containing:

• résumé/CV, including a list of publications,
• a general description of past research and future research interests (no more than three pages),
• contact information of at least two references,
• copy of the doctoral degree certificate, and other certificates/grades that you wish to be considered.