About the research project
The doctoral studentship position is within the doctoral programme in Resource Recovery and will be part of the research group Resource Management. The research project aims to develop and implement an AI-based smart bin to measure both the amount and type of food waste that is discarded. The implementation will primarily take place at a school, restaurant, or retirement home in Borås, Sweden.
The information collected using this smart bin will be used to identify which interventions can help reduce food waste. These interventions will then be implemented and the results will be analysed. The project thus contributes to the overall ambition to reduce the environmental impact of food waste.
Your work tasks
Own doctoral education within the abovementioned research project. The position includes both theoretical and experimental work with the development of an AI-based smart bin, with a focus on reducing food waste.
The research includes the development and implementation of the AI-based smart bin, identification of interventions to reduce food waste, implementation of these interventions, and analysis of the results. The research results will be disseminated, including through scientific publication.
In addition to doctoral studies, teaching in a relevant field or other departmental duties may be included with up to 20% of full-time. The total period of study for doctoral studies is then extended correspondingly.
Your qualifications
Employment is subject to the applicant’s meeting the eligibility requirements and being admitted to the doctoral programme. Admission will take place via the Research Education Committee for Resource Recovery.
To be admitted to doctoral education, a second-cycle degree (Master's degree or equivalent) is required. You must have documented knowledge in computer programming, computer modeling or another related field. Furthermore, you must be able to communicate well in written and spoken English.
The position also requires someone with good collaboration and initiative-taking qualities, an ability to work independently and in a structured way, as well as the ability to prioritise among different work tasks.
Merits
- Documented experience in advanced computer programming and/or the use of Gen-AI for object detection or similar.
- Experience in computational methods to study chemical or physical processes.
- Scientific publications in international, peer-reviewed journals.
Your employment
Type of employment: Fixed-term employment as a doctoral student according to the Higher Education Ordinance Chapter 5.
Employment rate: 100%
Start date: 1 October or as agreed.
Position location: Borås, Sweden
Reference number: PA2026/100
A new appointment as a doctoral student is valid for a maximum of one year, after which the appointment may be renewed for a maximum of two years at a time. Provisions regarding employment as a doctoral student can be found in the Higher Education Ordinance (1993:100), Chapter 5, Sections 1-7.
How to apply
Please submit your complete application including registration number and attachments via our recruitment system by 23 August (Swedish time, CET).
How to apply – create an account and see which documents you need to attach
The University of Borås welcomes applicants from all backgrounds, experiences, and perspectives, recognising that this enriches and strengthens our community. The University of Borås strives for even gender distribution among employees and values diversity.
Want to know more?
Doctoral education programme: Resource Recovery
Research Areas: Resource Recovery
Research Group: Resource Management
The University of Borås is a governmental authority, which means that you receive particular benefits, generous holiday leave, and a favourable occupational pension.
Benefits for employees
Work at UB
Contact those below if you want to know more. Please note that it may be more difficult to reach us during the holiday period:
about the position, Ilona Sárvári Horváth, recruiting manager
on the doctoral programme Resource Recovery, Päivi Ylitervo, Director of Studies
on the research team,Kim Bolton, research team leader
Trade union enquiries should be directed to:
Saco-S (union contact): Sunil Kumar, 033-435 40 00.
OFR/S (union contact): can be reached by email: [email protected]
We decline all direct contact with staffing and recruitment companies as well as sellers of recruitment advertisements.
