Open Position (s)
Tenure-Track Research Associate Position in Synthetic Biology
MICALIS Institute (INRAE, AgroParisTech, Université Paris-Saclay)
About the environment
The MICALIS Institute brings together over 350 researchers in microbiology and biotechnology. The recruiting team spearheads computational and experimental innovation in bioproduction, biosensing, and biocomputing, integrating AI‑driven design, end‑to‑end automated workflows, and a cell‑free biofoundry for rapid prototyping. Together, these assets drive synthetic biology R&D forward at an unprecedented pace.
Position overview
We seek a tenure‑track researcher specializing in synthetic biology, particularly with expertise in cell-free systems and cutting‑edge approaches such as artificial/synthetic cells. The candidate will enhance the cell‑free biofoundry and create a distinctive, complementary research program that aligns with the institute’s strengths in automation, AI/active learning, bioproduction, biosensing, and biocomputing.
Key responsibilities
- Lead an innovative, externally fundable research line based on artificial/synthetic cell research, including bottom‑up construction of minimal synthetic cells, artificial organelles (lipid‑ or protein‑based), and microcompartment systems
- Leverage and extend the cell‑free biofoundry to develop scalable methods for: Bioproduction (e.g., prototyping enzymes, ribosomal peptides, natural product pathways), Multiplex biosensing (e.g., cell‑free metabolic transducers), pathways and genetic circuits prototyping in vitro for rapid iteration
- Foster collaborations within MICALIS and across Paris‑Saclay, contributing to method sharing, workflow standardization, and FAIR principles.
- Supervise students and engage in broader educational missions (e.g., the mSSB master program www.mssb.fr).
What we offer
- A multidisciplinary institute with cutting‑edge automation and cell‑free platforms, and an open workflow ecosystem.
- Strong national/EU and industry networks, and a proven track record of competitive funding.
- A premiere environment to pioneer high‑impact research at the nexus of AI × automation × cell‑free synthetic biology.
Desired profile
- PhD (plus postdoctoral experience) in synthetic biology, biochemical engineering, molecular biology, or related fields.
- Demonstrated expertise in cell‑free systems (any subset): CFPS (lysate/PURE systems), TX/TL, metabolic prototyping, or biosensing.
- Familiarity with: Artificial/synthetic cells: bottom‑up construction, synthetic organelles, phase‑separated systems
- Additional strengths (any subset): DBTL/automation (robotics), AI/active learning for experimental design, metabolic biocomputing, FAIR workflows.
- A strong publication record, collaborative spirit, and excellent English communication skills.
Application materials (all in one PDF, please)
- CV, with notable publications and achievements.
- Names and contact details for at least two referees.
- Letter of motivation (~2–3 pages), detailing your proposed research program, highlighting how it leverages and complements the cell-free biofoundry and Micalis environment.
How to apply / Contact
Send applications or inquiries to jean-loup.faulon@inrae.fr. Applications will be reviewed on a rolling basis until the position is filled.
Equal opportunity
We welcome applications from all qualified candidates and are committed to fostering a diverse and inclusive research environment.
Research Associate Position: Data Science / Systems Biology
Context
We are seeking a motivated individual to join our research group within the MICALIS institute (INRAE & University of Paris-Saclay, website: https://www.micalis.fr), a leading research unit with over 350 researchers developing multidisciplinary approaches and promoting the development of synthetic biology for health and biotechnology.
The candidate will contribute to our ongoing efforts in developing cellular models, as highlighted in our recent publication (https://www.nature.com/articles/s41467-023-40380-0 and DOI: ), which proposes combining AI-driven and mechanistic methods to better design strains and predict strain performance more effectively.
The candidate will participate in projects funded by the French funding research agency (ANR) and a European Project at MICALIS. Within MICALIS , the recruiting research team (~20 staff spread into wet and dry labs) specializes in developing computer-aided design tools for biotechnology (more details at https://jfaulon.com/). The candidate will closely collaborate with software developers and interact with Research and Data Scientists, Engineers, and Ph.D. fellows.
Mission(s)
Begin work with innovative AI-driven whole-cell models designed to facilitate studies of transcription, translation, and metabolism. In this role, the candidate will undertake the following tasks:
- Participate in ANR-funded and European Project initiatives, aiming to enhance biotechnological applications through innovative cellular models.
- Benchmark existing mechanistic methods to model the kinetics of transcription, translation and metabolism.
- Contribute to the development of hybrid neural-mechanistic models based on physics-informed neural networks (PINNs) and/or graph neural networks (GNNs).
- Benchmark the hybrid models with experimental measurements collected by project partners or generated in the hosting lab.
- Develop strategies for applying hybrid models in cell engineering
Profile
- PhD. degree in System Biology, Data Science, Bioinformatics, Biophysics or a related field.
- Prior knowledge in metabolic networks, metabolomics, metabolic flux analysis or kinetics of transcription and translation is desired.
- Good programming skills in Python, testing practices, and Git versioning. Knowledge of continuous integration paradigms is a plus.
- Excellent communication skills and the ability to work effectively in an interdisciplinary team.
- Strong analytical skills and a keen interest in software development for biotechnological
Contract and Salary
- Fixed-term contract of 12 months (renewable), in accordance with French legislation.
- Salary will be commensurate with qualifications and experience.
To apply
Applicants should send a detailed curriculum vitae, a letter of intent explaining their motivations for the position, and contact details of at least two references.
Send your queries/applications to; Jean-Loup Faulon <jean-loup.faulon@inrae.fr>
