CAeSAR Project: CAR-DD: Cancer Advanced therapy through Rational Degrader Design

Université de Caen Normandie; France; Sur place; EUR 30 000 - 45 000; Plein temps

Résumé du poste

A research institution in France is seeking a research engineer to work on developing innovative anticancer drugs called degraders. This role focuses on designing compounds that selectively target the Mcl-1 protein, which plays a critical role in cancer cell resistance. Candidates should hold a PhD or equivalent in a relevant field and possess skills in bioinformatics, cheminformatics, or a related discipline. Applications are due by 31 January 2026, and should include a CV and motivation letter.

Qualifications

• PhD in a relevant field, such as computer science, biological sciences, or chemistry.
• Strong background in bioinformatics or cheminformatics.
• Familiarity with molecular modeling tools and structural data analysis.

Responsabilités

• Design and develop degraders targeting the Mcl-1 protein.
• Implement a multidisciplinary approach integrating molecular modeling.
• Expand the spectrum of exploited E3 ligases for therapeutic value.

Connaissances

bioinformatics

cheminformatics

basic computer skills

Formation

PhD or equivalent

Description du poste

Organisation/Company Université de Caen Normandie Research Field Computer science Biological sciences Chemistry Researcher Profile First Stage Researcher (R1) Positions Other Positions Country France Application Deadline 31 Jan 2026 - 23:59 (UTC) Type of Contract Temporary Job Status Full-time Offer Starting Date 1 Mar 2026 Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No

Offer Description

The CAR-DD project, for which we are recruiting a research engineer (IR) for a 12-month period, aims to develop a new generation of anticancer drugs called degraders (PROteolysis TArgeting Chimeras, PROTACs). These innovative molecules do not simply block a target: they induce its complete degradation via the cell’s natural recycling system, the proteasome. In this project, the target is Mcl-1, a protein that protects cancer cells from cell death. Its overexpression is frequent in various cancers (ovary, lung, lymphomas, pancreas) and represents a major mechanism of resistance to conventional treatments.

In this context, the work of the recruited IR will focus on the in silico design of degraders selectively targeting the Mcl-1 protein. He or she will implement a multidisciplinary approach integrating molecular modeling tools and available structural data analysis. The objective is to identify innovative combinations of warheads directed against Mcl-1, suitable linkers, and E3 ligase ligands capable of inducing effective and selective degradation of Mcl-1.

Beyond optimizing PROTAC combinations, this project aims to expand the spectrum of exploited E3 ligases, currently limited to around fifteen (including CRBN, VHL, MDM2, and DCAF15), while more than 600 E3 ligases exist in the human genome. This limitation is largely due to the lack of high-quality ligands targeting other E3 ligases, despite their potential in terms of tissue-specific expression and therapeutic value. The recruited IR will therefore engage in an exploratory approach to predict binding sites on alternative E3 ligases and identify new E3 ligase ligands, relying on druggable pocket detection methods and in silico screening. Expanding this panel of ligases represents a strategic lever to design more specific degraders, less prone to resistance, and fully compatible with the requirements of precision medicine in oncology.

Where to apply

E-mail [e-mail]

Requirements

Research Field Computer science Education Level PhD or equivalent

Research Field Biological sciences Education Level PhD or equivalent

Research Field Chemistry Education Level PhD or equivalent

Skills/Qualifications

Desired profile: bioinformatician, chemoinformatician, or biologist/chemist with basic computer skills.

Additional Information

Selection process

Applications should be sent to Prof. Jana Sopkova-de Oliveira Santos ([e-mail] ) before 31/01/2026 and must include a detailed CV, a motivation letter, and one or more reference letters, including the PhD supervisor’s reference.