The Department of Biotechnology in collaboration with The Department of Information Technology at the University of Turku is seeking two postdoctoral researchers or PhD students/project researchers for a two-year fixed-term positions in a project aimed at improving the energy efficiency of indoor farming. The project is funded by the Future Makers Programme of the Technology Industries of Finland Centennial Foundationand and is related to the fields of photosynthesis research and information technology. The project will run for two years. The work is full-time and will start as soon as possible as agreed.

The aim of the research is to find ways to reduce the energy consumption of artificial lighting in indoor farming by combining photosynthesis research and machine learning

Indoor faming is a fast-growing business sector that enables water-, nutrient- and land-efficient local crop production independent of weather conditions. Locally produced year-round vegetables are of great importance to today's consumers, while new indoor farming technologies are expected to have an important role in the adaptation to global and climate change. The limiting factor for the growth of the sector is the high energy demand for artificial lighting. The project will combine deep photosynthesis research knowledge on the factors determining the plant light use efficiency with optimisation of conditions using machine learning. At the heart of the project is a new controlled conditions research platform that enables measurement of plant light use efficiency and machine learning-based feedbackcontrol of light and conditions. The aim is to maximise yield and minimise energy consumption and to gain information from processes affecting the efficiency.

Job description: Applicants are required to have theoretical and practical knowledge

This is an interdisciplinary project using new research technologies, requiring the ability to work across disciplines (photosynthesis and information technology), independently and as part of a research team. Applicants will communicate and collaborate with each other during both the design and implementation phases of the project. In addition to theoretical work, both tasks will involve practical laboratory work and the development of research equipment. Applicants must be fluent in English and able to work in a dynamic environment on their own initiative. One of the researchers will work primarily on adaptive control and machine learning (Task 1), while the other will focus on growth experiments and research on factors affecting the light use efficiency of a plant (cyanobacterium) (Task 2).

Task 1: Applicants working on adaptive control and machine learning must have a background in an appropriate computational science. A basic understanding of biological systems and how to optimise biological processes is an advantage. The job requires knowledge of control theory, adaptive control and machine learning based data analytics. Experience in discrete optimization is also an advantage. Practical experience in adaptive control and machine learning, experience in programming languages related to computer science and control theory (e.g. Python, Matlab), knowledge of IoT devices and embedded systems, and a good track record of publications would be an asset.

Task 2: Working with growth experiments and factors affecting light use efficiency, the researcher is expected to have a good understanding of the structure, function and regulation of the photosynthetic machinery in plants and cyanobacteria. The applicant should understand the regulatory responses to changes in light quantity and quality in the photosynthetic machinery and how the function of the photosynthetic machinery is linked to the functioning of the whole plant. Previous experience in the use of photosynthesis research equipment based on gas exchange and optical signal measurements as well as wet lab skills, and the ability to apply this knowledge to the implementation of new research equipment will be considered an advantage. A basic understanding of IoT devices and programming languages is beneficial for the conduct of work.

The qualification requirements of the positions are stated in the University of Turku Rules of Procedure: https://www.utu.fi/en/university/organisation

A person selected for the position of postdoctoral researcher is required to have a doctoral degree and the ability to conduct independent scientific work as well as having the necessary teaching skills.

A person selected for the post of doctoral researcher/project researcher is required to have a higher university degree. The degree must be completed by the end of the application period. If the person does not have a Master degree yet, the title will be research assistant. If the selected person already has a right to pursue a doctoral degree at the University of Turku, (s)he must also have an accepted research plan. In addition, when acquiring his or her degree or otherwise, he or she is required to have demonstrated the ability and motivation to undertake postgraduate studies and the capacity to complete a doctoral degree in accordance with the research plan.

The salary is determined in accordance with the university salary system for teaching and research personnel. The salary for a doctoral researcher/project researcher will be in average 2300 - 2700 euro/month and for a post-doctoral researcher in average 3300 - 3600 euro/month depending on competence and experience.

A six (6) month trial period applies to the positions. Also good English language competence is required.

Applications must be submitted at the latest on 9.4.2023 using the electronic application form of the University of Turku on the following address: https://www.utu.fi/careers

The link to the application system is at the beginning of this announcement (“Apply for the job”).

Applicants should enclose with their application a CV, short cover letter including a short description of applicant’s relevant skills, knowledge and motivation for the post, degree certificate(s), list of publications (if applicable) and other documents that may influence the filling of the position.

For further information about the positions please contact project leader, assistant professor Mikko Tikkanen (misati(at)utu.fi). For the job related to adaptive control and machine learning  please contact professor Jukka Heikkonen (jukhei(at)utu.fi) and for the job related photosynthesis please contact either assistant professor Mikko Tikkanen (misati(at)utu.fi) or associate professor. Pauli Kallio (pataka(at)utu.fi). Regarding the recruitment process technical matters, if needed please contact biocityhrservices(at)utu.fi.

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