Lecturer-researcher scientist bioinformatic and artificial intelligence

Teaching

The recruited candidate will contribute their expertise to the initial training of engineering students and master's students by teaching in the following areas:

• Bioinformatics,

• Machine learning and pattern recognition,

• Artificial intelligence applied to biology, particularly in the fields of nutrition and food safety.

and developing and teaching thematic summer schools in bioinformatics.

The recruited candidate will also be involved in curriculum design and the development of teaching content.

More specifically, the recruited candidate is expected to contribute to enriching the range of courses taught in English.

The recruited candidate will be expected to reflect on the evolution of core curriculum, specialization tracks, and master's programs, with the aim of advancing UTC’s educational offering in artificial intelligence applied to biology and in bioinformatics.

Research

The research assignments fall within one of the strategic areas of the GEC laboratory, focused on genomic and post-genomic technologies and the development of artificial intelligence applied to the life sciences, particularly in the fields of personalized nutrition, food quality and safety, and health:

• Develop and test artificial intelligence models applied to the analysis of post-genomic, metabolomic, and microbiota data originating from GEC projects and those of the Sorbonne University Alliance, including the Global Health Institute, among others.

• Lead the implementation of integrated methodological frameworks (machine learning, multi-omics

networks, generative AI) for analyzing genotype–phenotype–environment interactions.

• Participate in drafting research project proposals, particularly in response to European Commission

calls for projects (e.g. Horizon Europe).

The recruited candidate will be expected to play an active role in the development and scientific coordination of one of UTC’s four new interdisciplinary thematic research centers, working transversally across all UTC research laboratories. These centers aim to be distinctive, visible, and attractive; capable of structuring consortia; attracting public and private partners; and preparing coordinated responses to national and European project calls. The specific center concerned here is the Artificial Intelligence and Technological Systems Center.

Finally, the recruited candidate will be expected to build concrete bridges between this UTC interdisciplinary research center and the PostGenAI@Paris research program, in which UTC is a partner. This program is hosted within the Sorbonne Cluster for Artificial Intelligence (SCAI) of the Sorbonne University Alliance, of which UTC is a founding member.

Technology transfer and Partnerships

• Identify and initiate industry collaborations in applied AI, bioinformatics, and machine learning,

particularly in the agri-food, biotech, and healthcare sectors.

• Strengthen national partnerships in the Hauts-de-France region, within the UT group and the

Sorbonne University Alliance, as well as UTC’s international collaborations, by exploring funding

mechanisms for internships and joint PhD supervision of bilateral projects with partner institutions.

Additional information

Additional activities

Participate in the implementation of the UTC Sustainable Development & Social and Environmental Responsability (SD&SER) Master plan.

Ressources

The recruited candidate will be provided with all the necessary resources to carry out their duties: office space, computer equipment, access to institutional digital resources, and the possibility to acquire pedagogical and scientific materials (books, software, licenses, etc.).

The recruited candidate will benefit from the scientific environment of the GEC laboratory (UMR CNRS

7025), including its analytical platforms, such as the Food Sciences Platform and the Bioinformatics Platform.

Furthermore, in 2026, UTC will deploy a state-of-the-art scientific computing and storage infrastructure, comprising a high-memory, GPU-enabled HPC computing node and a modular, scalable RAID-based storage system, specifically designed to support research in bioinformatics, artificial intelligence, and data science.

This infrastructure will enable, among other things:

• the processing of large-scale multi-omics datasets,

• the use of intensive bioinformatics pipelines,

• the development of AI and deep learning models,

• the analysis of biological images, and

• the implementation of large-scale interdisciplinary projects.

In the longer term, a potential subsequent employment opportunity (through external funding or a permanent position) on the same topic is under consideration and could enable a long-term collaboration.

The institution

The université de technologie de Compiègne (UTC), a member of the Sorbonne University Alliance (ASU) and the network of universities of technology (UT), is ranked among the top French engineering schools in a number of national rankings, and offers a particularly favorable environment for teaching and research.

https://www.utc.fr/en/

The Department

Among the six departments at UTC, the Biological Engineering Department offers courses:

• in the core curriculum (integrated preparatory cycle);

• in the engineering cycle (initial and continuing education);

• at the graduate level (Master’s and PhD programs).

The department’s academic programs focus on technologies related to medical devices, biotechnologies, food innovation, and agri-resources. It hosts two research laboratories:

• Biomechanics and Bioengineering Laboratory (BMBI – UMR CNRS 7338)

• Enzyme and Cell Engineering Laboratory (GEC – UMR CNRS 7025)

The department maintains strong ties with industry, both in education, through student internships (assistant engineer, engineer, master's level, etc.) and in research, through collaborative research projects.

It also fosters close relationships with national and international institutions, through student exchange agreements and collaborative research initiatives.

https://www.utc.fr/en/courses-and-training/the-utc-engineering-diploma/biological-engineering/

The Laboratory

The Enzyme and Cell Engineering Laboratory (GEC) is a joint research unit affiliated with the CNRS – UMR 7025, and part of the CNRS Institute of Biological Sciences. The GEC unit is bi-located between Compiègne (UTC) and Amiens (UPJV). It includes 19 faculty members and researchers, as well as 16 technical support staff (engineers, assistant engineers, and technicians).

The GEC unit has nationally and internationally recognized expertise in biotechnology. Its research activities aim to understand and master living systems through various approaches, including molecular dynamics, simulation, and data decryption, supported by artificial intelligence.

The unit’s areas of investigation are broad: its expertise spans biological models of plant, animal, fungal, and bacterial origin, and covers a wide range of molecular systems with varying levels of complexity.

Research is supported by cutting-edge platforms and technical facilities equipped with advanced instrumentation.

https://gec-upjv.utc.fr/en/

Contract type and excepted start date

Fixed-term contract, expected duration of 18 months, to be filled in June 2026. Renewable, subject to funding availability.

Gross monthly salary

From € 3000 to € 6000, depending on experience and funding

Application dates

From 06/03/2026 to 07/04/2026

Contacts

Frederic Lamarque, Director of Research at UTC

frederic.lamarque@utc.fr

Sofiane Boudaoud, Head of the Bioengineering Department

sofiane.boudaoud@utc.fr

Bérangère Bihan-Avalle, Director of the GEC Laboratory

berangere.avalle@utc.fr

Profile and keywords

Profile: bioinformatic and artificial intelligence

Keywords: bioinformatics, artificial intelligence, functional genomics, or data science.

Qualification, education

Experienced academic holding a PhD in bioinformatics, artificial intelligence, functional genomics, or data science, with a recognised track record in leading European and international projects.

The candidate should demonstrate strong expertise in multi-omics approaches, AI applied to life sciences, and solid command of bioinformatics platforms and software environments.

They must possess a proven ability to work in interdisciplinary environments, to supervise research teams and PhD students, and to structure collaborative scientific dynamics.

The candidate should also have extensive experience in developing educational content, supervising students, and taking on academic responsibilities (e.g., courses, Master’s programs).

Proven international experience, a strong culture of collaborative research, engagement in applied research connected to socio-economic sectors, and a sensitivity to sustainability issues are highly valued.

The candidate is expected to demonstrate openness, adaptability, and scientific leadership, with the ability to initiate, structure, and strengthen national and international scientific and technological collaborations.

Fluency in English is essential.