Doctoral researcher in AI and sustainable food systems

Are you interested in data-driven research involving AI, digitalisation, and sustainable food systems? We are looking for a doctoral researcher to join the CIRC4FOOD project, an international European consortium developing digital infrastructure, FAIR data systems, and AI-based modelling tools for circular food production.

What your work will be like

Your work will focus on developing data-driven and AI-based models for circular food production in close collaboration with international partners. The role involves developing modelling approaches for food and bioprocess systems, managing and analysing research data according to FAIR data principles, and supporting project partners in capturing and utilising relevant food process information. You will also take part in joint research activities within the consortium.

As a doctoral researcher, your primary goal is to complete your doctoral degree. This includes publishing peer-reviewed scientific articles – typically approximately one publication per year – and completing the required doctoral studies.

You will also participate in conferences, seminars, and research dissemination. Depending on your interests and experience, you may contribute to teaching and supervise bachelors and masters students.

You will work closely with your supervisor through regular weekly meetings and collaborate with international partners on a monthly basis. Supervision is provided by Assistant Professor Samuel Perez Vega together with a computational science expert at LUT University.

The position may involve occasional travel for project meetings, workshops, and conferences.

The position is based in the Systemic Food Processing research group at LUT. The group is part of the Department of Separation Science, one of the largest academic research environments in Northern Europe focusing on separation and purification technologies. The department develops sustainable technologies and digital solutions supporting the transition toward resource-efficient industrial systems, with strong activity in food systems, bioprocessing, water treatment, bioeconomy, and advanced process engineering. Research is carried out in an interdisciplinary environment integrating chemical engineering, food science, biotechnology, digital systems, and sustainability science to address global challenges related to food security, climate change, and industrial sustainability.

The role is part of a consortium of approximately 20 partners, offering opportunities for multidisciplinary collaboration in circular food systems and related areas.

The selected candidate must apply for the right to pursue doctoral studies at the LUT Doctoral School within the first two months of employment.

What we expect

You have a masters degree in computer science, computational modelling, data science, food engineering, chemical engineering, food science, or a related field. In addition, the role requires commitment to completing your doctoral studies within the normative duration of the degree.

We are seeking a candidate with a strong interest in sustainable food systems, digital transformation, the circular economy, and data-driven technologies for food and bioprocess engineering. Prior experience is an advantage, but early-career candidates are also encouraged to apply if they are eager to learn and take initiative.

You will contribute to interdisciplinary research focusing on FAIR data-driven approaches and modelling methods for circular food systems. We particularly value experience in artificial intelligence, machine learning, and data-driven systems as well as strong programming and modelling skills (e.g., Python, PyTorch, MATLAB, or R). Experience in process modelling, simulation, or optimisation is also an advantage.

Familiarity with research data management, FAIR principles, and open science practices is beneficial. We welcome interest in food systems, process engineering, and the circular economy as well as experience in sustainability assessment or life cycle assessment.

Strong analytical and problem-solving skills are essential. You should be able to work independently, communicate findings clearly, and collaborate effectively in an international research environment. Excellent written and spoken English is required.

What we offer

We offer a collaborative research environment where you will contribute to an ongoing EU research project, develop your academic publication record, and receive close supervision throughout your doctoral studies.

The employment relationship starts with a one-year term including a six-month trial period. The contract may be extended by three years if progress in studies and research in the first year is satisfactory.

The start date is in October 2026 (negotiable). The position is based at LUTs Kouvola campus in Finland, with hybrid working options available. Regular presence on campus is required.

The hours are flexible and support work-life balance. The position follows a system of 1,612 annual working hours in accordance with the collective agreement for Finnish universities.

The salary is based on the Finnish university pay systems scale for teaching and research staff (requirement level 2). The starting salary is approximately EUR 3,100 per month, depending on experience and qualifications.

Interested? Please submit your application by 26 July 2026 #_msocom_1 at midnight, Finnish local time (UTC+2h). Fill out the online application form and attach the following documents in English and in PDF format:

• Motivation letter (one-page) highlighting your research skills relevant to the position and describing why you are interested in and suitable for the position.
• Curriculum vitae (CV) following the guidelines of the Finnish Advisory Board on Research Integrity.
• Scanned copies of your original bachelors and masters degree certificates and transcripts of records. If the original documents are not in English, each document must be accompanied by an official certified translation into English. If your degree is still unfinished, provide an official estimate of your graduation date confirmed by your supervisor or school.
• List of publications.
• Contact details of two references.

Only applications that include the required documents will be