The University of Agder has more than 1500 employees and almost 14 000 students. This makes us one of the largest workplaces in Southern Norway. Our staff research, teach and disseminate knowledge from a variety of academic fields. Co-creation of knowledge is our common vision. We offer a broad range of study programmes in many fields. We are situated at two modern campuses in Kristiansand and Grimstad respectively.
We are an open and inclusive university marked by a culture of cooperation. The aim of the university is to further develop education and research at a high international level.
About the position
A fixed-term 100 % position is available at the University of Agder, Faculty of Engineering and Sciences as a Post-doctoral Research Fellow in Deep Learning for Sustainable and Intelligent Geographic Analysis, affiliated to the Department of ICT, for a period of 3 years. The position is primarily based in Grimstad, Norway. However, the candidate is expected to spend significant time collaborating with research partners in Kristiansand, Norway.
The starting date is negotiable with the Faculty.
This open position is affiliated with the Centre for Artificial Intelligence Research (CAIR) at the University of Agder and is closely associated with partners from a funded research project led by Kristiansand Municipality. The key project collaborators include Norkart, Kartverket, and the University of Agder. The main goal of the project is to streamline municipal work processes related to the land registry and building permit processing using automated, advanced data-driven methods, including artificial intelligence in combination with proactive citizen/case-worker dialogue. This contributes to the progression of sustainable mapping technologies.
The candidate's main responsibility will be to explore the potential of deep learning-based systems in supporting the above-mentioned tasks . This includes, but not limited to; predicting and interpreting map data features using Convolutional Neural Networks (ConvNets), predicting the outcome of permit applications using archival data and multi-modal models / LLMs and achieve high degree of trust in deep-learning models used in government work processes. Tasks will include working with image data, sequential inputs from geolocation sensors, intermediary categories, and environmental logs. The candidate will also investigate the use of associated and contextual data, including data from the municipality case management system, time-series behavioral information, and other data pertinent to mapping and geographical analysis.
Achieving these goals requires new technology and knowledge related to AI/machine learning encompassing multimodal data sources across today's "data silos". To ensure quality-controlled case processing, the candidate will need to employ data-driven and advanced technology with proactive involvement from the citizens.
The main research challenges revolve around integrating diverse data types and developing robust, scalable models that can handle the intricacies of geographical and environmental data. The candidate will face key issues, such as dealing with high-dimensional spatial and temporal data, managing noisy or incomplete data from various sources, and creating predictive models that can learn and adapt to changing conditions. They will need innovative thinking and the capability to develop novel solutions to apply deep learning techniques to geospatial analysis - a field where these techniques are not commonly utilized. The research will also have to tackle the challenge of making analysis results interpretable and actionable for end-users. This introduces an additional layer of complexity, requiring a deep understanding not only of AI and machine learning models but also of the user needs and contexts in which these technologies will be deployed.
The ideal candidate will bring expertise in the following areas:
Software development
Machine Learning, particularly focusing on Deep Neural Networks and machine vision techniques
Understanding and implementation of Transformers, in particular in multimodule situations.
Natural Language Processing, with a special emphasis on Large Language Model Learning (LLMs)
Geographical Information Systems (GIS)
Emphasis will be placed upon the project description and the relevance it has with regard to the subject in question and the research environment at the Faculty.
Personal qualities
Personal suitability, good teamwork skills, inventiveness, and a proactive approach, will be emphasized in the evaluation as well as relevant practical experience. The candidate will be expected to contribute to an active research community that promotes the personal and professional growth of the candidate. The position places great demands on the applicant’s capacity for independent goal-oriented work, ability to concentrate and attention to detail.
We offer
professional development in a large, exciting and socially influential organisation
a positive, inclusive and diverse working environment
modern facilities and a comprehensive set of welfare offers
The position is remunerated according to the State Salary Scale, salary plan 17.510, code 1352, NOK 563 900 – 626 100 gross salary per year. Higher salary grades may be considered for particularly well-qualified applicants. A compulsory pension contribution to the Norwegian Public Service Pension Fund is deducted from the pay according to current statutory provisions.
General information
UiA is an open and inclusive university. We believe that diversity enriches the workplace and makes us better. We, therefore, encourage qualified candidates to apply for the position independent of gender, age, cultural background, disability or an incomplete CV.
Women are strongly encouraged to apply for the position.
The successful applicant will have rights and obligations in accordance with the current regulations for the position, and organisational changes and changes in the duties and responsibilities of the position must be expected. The engagement is to be made in accordance with the regulations in force concerning the acts relating to Control of Export of Strategic Goods, Services and Technology. Appointment is made by the University of Agder’s Appointments Committee for Teaching and Research Positions.
Short-listed applicants will be invited for interview. With the applicant’s permission, UiA will also conduct a reference check before appointment. Read more about the employment process.
In accordance with the Freedom of Information Act § 25 (2), applicants may request that they are not identified in the open list of applicants. The University, however, reserves the right to publish the names of applicants. Applicants will be advised of the University’s intention to exercise this right.
Application
The application and any necessary information about education and experience (including diplomas and certificates) are to be sent electronically. Use the link "Apply for this job".
The following documentation must be uploaded electronically:
Certificates with grades
List of publications
Doctoral thesis
Up to 10 academic articles and R&D projects which the candidate wishes to particularly emphasise for the assessment process
A description of the applicant’s research interests, the background for the thesis question that the applicant wishes to work on, and its relevance for the advertised position. A brief overview of relevant research pertaining to the design of assignments and relevant issues for research should also be included here
Project plan
Any other relevant documentation
The applicant is fully responsible for submitting complete digital documentation before the closing date. All documentation must be available in a Scandinavian language or English.
