Structural Bioinformatics Engineer

This recruitment is part of the ORIGAMI project, entitled ‘Rational design of functional single-stranded oligonucleotides via reverse folding for biotechnological applications’, funded by the Pre-Maturation Programme of the Sorbonne University Alliance’s University Innovation Cluster.

Role

The successful candidate will participate in research activities focused on the development of a digital workflow for the reverse folding of single-stranded oligonucleotides.

Activities

• In silico molecular modelling

• Stochastic modelling

• In silico protocol optimisation

• Coding

• Literature review

Background

Single-stranded nucleic acids (ssNAs), a highly powerful biotechnological tool, are capable of specifically and selectively recognising molecules thanks to the 3D structures they adopt. Therefore, the design of ssNAs for therapeutic or diagnostic purposes requires the identification of all ssNA sequences that fold into a target structure (inverse folding). Digital inverse folding tools do exist, but they are limited to providing few results, without accompanying them with a measure of the quality of the sequence provided, and they focus on the 2D structure. We will provide a comprehensive and generalisable procedure, accessible via a web server, combining numerical and computational methods with experimental validation to design ssNA sequences with a desired 3D structure and function. The first application will focus on the design of patentable ssNAs for the diagnosis of Lyme disease.

ADDITIONAL INFORMATION

Application dates

From 16/03/2026 to 15/04/2026

Contract type and expected start date

Fixed-term contract for 13 months, ending no later than 30/09/2027

Gross monthly salary

Depending on experience and funding

Working hours

37 hours and 30 minutes per week – 1,607 hours per year

Working environment and context

The successful candidate will join the CNRS UMR 7025 Enzyme and Cell Engineering (GEC) unit – Department of Biological Engineering (GB) – and will work in collaboration with the Compiègne Laboratory of Applied Mathematics (LMAC).

They will report to the project leader, maintain regular communication with them and work closely with all relevant stakeholders.

A workstation suitable for bioinformatics work will be made available to the successful candidate.

Qualifications, training and accreditation

Qualification: Master’s degree (2 years)

Field: bioinformatics, applied mathematics

Skills

Stochastic modelling/machine learning

Molecular modelling

English: minimum B2 level

Programming (Python)