PhD Position in Computational Physics: Engineering New RubisCO Proteins
Fully funded PhD fellowship to design next-generation RubisCO enzymes using physics-informed AI and experimental validation.
Best for:Best for master’s graduates in computational physics, biophysics, or bioengineering with expertise in statistical modeling, AI, and a passion for interdisciplinary research at the physics-biology interface.
Overview
This PhD position at the Laboratory for Physics and Engineering of Nanostructures (LPENS) within PSL University focuses on computational design of novel RubisCO enzymes with enhanced CO₂ catalytic activity. The project combines statistical physics, generative AI, and experimental biology to overcome evolutionary constraints in photosynthesis. The successful candidate will develop predictive models to navigate RubisCO’s sequence-function landscape, collaborate with biochemistry and synthetic biology labs, and validate designs in vivo using Chlamydomonas algae. The programme offers interdisciplinary training, international mobility (including a 3-month secondment at the University of Chicago), and exposure to startup ecosystems. Fully funded by the Horizon Europe MSCA COFUND PRISM programme, this role is ideal for master’s graduates with strong computational and physics backgrounds.
What you'll do
- Develop physics-grounded and data-driven models to predict RubisCO sequence-function relationships and catalytic performance.
- Design novel RubisCO variants using interpretable AI models, prioritizing variants for experimental validation.
- Collaborate with biochemistry and synthetic biology labs to test AI-designed RubisCO variants in vivo using Chlamydomonas algae.
- Conduct a 3-month secondment at the University of Chicago to integrate advanced computational methods for epistasis mapping.
- Iteratively refine models using experimental data from algal evolution studies and directed evolution experiments.
- Engage with industry partners and startup ecosystems to explore valorization opportunities for synthetic biology innovations.
- Participate in interdisciplinary training modules on sustainability, innovation, entrepreneurship, and career development.
Requirements
Degree required: Master’s degree or equivalent in Physics, Computational Biology, Bioengineering, or a related quantitative discipline
Degree offered: PhD
Language: English; excellent proficiency (written and spoken) for collaboration and reporting
Instruction: English
- Proven expertise in statistical physics, computational modeling, or machine learning for biological systems
- Strong programming skills (Python, R, or equivalent) for implementing AI/ML models
- Experience with bioinformatics tools or protein sequence/structure analysis
- Familiarity with experimental biology concepts (e.g., directed evolution, Chlamydomonas algae systems)
- Excellent written and spoken English proficiency for international collaboration
- Open to international applicants (no nationality restrictions)
- Applicants must not have resided or carried out their main activity (e.g., work, studies) in France for more than 12 months in the 3 years prior to the deadline
- Maximum of 4 years prior research experience (consistent with MSCA eligibility rules)
- No upper age limit for MSCA COFUND fellows
Funding & terms
How to apply
Deadline: 2026-10-31 (Europe/Paris)
Applicants must submit their application through the official PRISM programme website. The process involves uploading a CV, cover letter, research proposal, academic transcripts, and two reference letters. Additional documents may be requested based on the application review. The deadline for submissions is 23:59 Paris time on October 31, 2026.
- Curriculum Vitae (CV)
- Cover letter detailing motivation and fit for the project
- Research proposal outlining the applicant’s approach to the PhD topic
- Academic transcripts and degree certificates
- Two reference letters from academic or professional referees
- Proof of English proficiency (if not from an English-speaking institution)
Contact
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