PhD Research Fellow in Vision-Language Models in Remote Sensing
Deadline: 01.02.2024
University of Agder
The University of Agder has more than 1500 employees and almost 14 000 students, making us one of Southern Norway's largest workplaces. Our dedicated staff engage in research, teaching and dissemination across a diverse range of fields.
The university is located on two modern campuses in Kristiansand and Grimstad.
About the position
A fixed-term 100% position is available at the University of Agder, Faculty of Engineering and Science as a PhD Research Fellow in Vision-Language Models in Remote Sensing, affiliated to the Department of Information and Communication Technology, for a period of three years. The position is located, at the present, at Campus Grimstad. The starting date is negotiable with the Faculty.
Responsibilities
Vision-language models achieve outstanding performances in recognizing objects in an image, inferring their relationships, and generating image descriptions in natural languages. They're ideal for tasks like image captioning, text-based image retrieval, and visual question answering. Their application in remote sensing for semantic understanding of objects and relationships is a growing research field. This is an exciting opportunity to contribute to the development of new vision-language models at the frontiers of remote sensing. Research topics for the PhD Research Fellow include, but are not limited to the following:
The ideal candidate will have expertise in one or more of the following:
Computer Vision
Natural Language Processing
Remote Sensing
Deep Learning
Reinforcement Learning
Large Language Models
Vision-Language Models
Required qualifications
Master’s degree in ICT, Computer Science, Electrical and Computer Engineering, or a similar/related field and documented competence in areas relevant to the position. Candidates who are in the final stage of the master’s education within the relevant field may also be considered, given that a master’s degree is to be achieved before the enrollment of this position. Applications from applicants who already hold a PhD will normally not be considered.
Strong academic credentials
The ideal candidate will have technical expertise in one or more of the following areas:
Computer Vision
Natural Language Processing
Remote Sensing
Deep Learning
Reinforcement Learning
Large Language Models
Vision-Language Models
Written and spoken English proficiency. International candidates that are not exempt from the English language requirements pursuant to the guidelines of the Norwegian Agency for Quality Assurance in Education (NOKUT) must document this through one of the following tests with the stated results or better:
TOEFL - Test of English as a Foreign Language with a minimum score of 600 for the Paperbased Test (PBT), or 92 for the Internet-based Test (iBT)
IELTS - International English Language Testing System, with the result of 6.5
Applicants will be assessed on the basis of academic background and results, attainment, and any previous research and development work.
The position is remunerated according to the State Salary Scale, salary plan 17.515, code 1017 PhD Research Fellow, NOK 532 200 gross salary per year. 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 the 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
Master’s thesis/ Summary (approximately 1-2 pages) of the master's thesis; For those who are in the final stage of the Master’s education but without a Master’s degree yet, the transcripts without the results of thesis can be provided; The evaluation result of the thesis can be provided later.
Applicants with a foreign higher education must attach an official description of the grading system used at the issuing institution;
Academic work and R&D projects, as well as a list of these
Summary or links to the applicant's scientific publications (if any);
Project description with a maximum scope of x pages, including reference list. The outline should present and discuss possible research questions, theory perspectives, material, a progress plan, and methods within the given framework
Applicants who are required to document their English proficiency must submit their TOEFL or IELTS test results (these may be forwarded after the closing date);
References
The applicant is fully responsible for submitting complete digital documentation before the closing date. All documentation must be available in English or in a Scandinavian language.
