The position is based in our Paris Office, with an ideal start date in April / May 2025. Please apply in English.
About the role:
The Owkin Biomedical Department aims at making novel biomedical discoveries building on high-quality, multi-modal patient datasets, multi-modal preclinical models and Artificial Intelligence (AI). At Owkin, we utilize AI to unlock the power of spatial transcriptomics, single-cell and bulk RNA, H&E images, whole exome sequencing and preclinical models for novel Target Discovery, biomarker selection and drug repositioning in the field of Oncology.
The Biomedical Discovery group of Owkin is looking for a passionate research intern to work on Target discovery in oncology.
As part of the project, the intern will have the opportunity to contribute to the development of a novel predictive AI model using AI agents, by defining disease-relevant preclinical models that best reflect a specific tumor type, with a key focus on integrating complex disease models. The intern will actively participate in defining strategies that leverages curated experimental datasets—sourced from both peer-reviewed literature and in-house experimental studies —spanning patient-derived cellular, 3D organotypic and preclinicalin vivo models, with Owkin spatial and scRNA data for Target discovery.
The candidate will assess and rank outputs from our Internal Discovery engines based on defined biological criteria. The role also includes building on Klinical Match to allow an accurate model selection for validation and consequently accelerate translational research and support the development of more clinically relevant cancer models. Therefore, the intern will have the opportunity to evaluate candidates in early stages of experimental validation by critically evaluating experimental design and results from external partners as well as identifying suitable mechanistic hypotheses for positive target candidates. We expect the intern to collaborate closely with the multidisciplinary teams including R&Tech (research & technology), Biomedical and external partners.
This internship provides a unique opportunity to gain experience in the use of next generation preclinical models and technologies coupled with AI for target discovery in oncology.
In Particular, you will:
- Perform in-depth biological assessment on experimental design, results and interpretation of wet-lab experimental readouts datasets (OrganoidDB, PDXO/HUB, PDX consortium, MSH-GEMMs) especially involving complex disease models, with particular focus on treatment response data.
- Implement, adapt and run internally developed predictive models to align and map the most relevant experimental models to patient subgroups
- Contribute to Klinical Match (K-Match) Discovery by integrating patient-derived preclinical models with spatial, single-cell RNA-seq, and proteomics from Owkin curated datasets (in 1 oncology indication)
- Support initial framework of validation of our K-Match Model Selection Agent
- Support Target candidates prioritisation from our Discovery Engine.
- Contribute to regular research reviews on the indication of interest and use of patient-derived experimental models and spatial & single cell technologies for target discovery and validation.
- Participate and present findings in group meetings.
- Submit a final Report of your findings.
About you
Required qualifications / experience:
- MSc year 2+ level in oncology, molecular biology, immunology, immuno-oncology.
- Knowledge about tumor biology and the tumor microenvironment.
- Experience in techniques such molecular biology, genetic engineering technologies.
- Motivation to work at the intersection of biology and AI
- Excellent in written and oral communication skills
- Fluent in English (spoken and written)
- Highly organized and meticulous about details; capable of tackling complex problems logically and effectively; fun to work with; honest; excited to work in a dynamic, fast-paced environment
- Authorization to work legally in France
Preferred qualifications/bonus:
- Experience in working with any of the following preclinical models and/or technologies: cellular screenings, organoids, 3D models, preclinical models, single cell, spatial transcriptomics, whole exome sequencing.
- Previous work on Target discovery projects
- Knowledge in immuno-oncology and preclinical models
- Contribution to publications in conferences and journals
