Multiomics AI

Start Date: November / December 2026 (ASAP)

Reporting to: Founder & CEO

Company Description

Multiomics AI & Bioinformatics Engineer (M/F) – Precision Oncology

Company: Rosetta Omics

Location: Paris / Île-de-France, France

Contract: Full-time – 12-month fixed-term contract (CDD)

Start Date: November / December 2026 (ASAP)

Reporting to: Founder & CEO

Company Description

Rosetta Omics aims to revolutionize cancer treatment by unlocking the full potential of precision medicine through the integration of multiomics, spatial biology, and artificial intelligence.

With more than 20 million new cancer cases diagnosed globally each year, there is an urgent need for more effective and personalized treatment strategies to improve patient survival while reducing the costs associated with ineffective therapies.

By advancing the ability to predict patients' responses to treatments, Rosetta Omics empowers physicians with deeper molecular insights to guide therapeutic decisions and deliver the most effective care to each patient as early as possible.

The company's mission is to accelerate the transition toward a future where precision medicine becomes the standard of care for cancer patients worldwide.

Rosetta Omics is a laureate of the France 2030 AI Pioneers program (2026), recognizing its innovative approach at the intersection of biotechnology, artificial intelligence, and healthcare.

Role Description

We are seeking a highly motivated and experienced Multiomics AI & Bioinformatics Engineer to join our growing team in Paris / Île-de-France.

This is a full-time, 12-month CDD position, starting in November or December 2026.

Working closely with the Founder & CEO, scientific team, and clinical research partners, the successful candidate will play a central role in developing and implementing advanced bioinformatics and artificial intelligence solutions for precision oncology.

The primary mission will be to analyze and integrate complex multiomics datasets, develop machine learning models to predict cancer treatment responses, and identify clinically relevant biomarkers.

The ideal candidate combines strong computational and analytical expertise with a deep understanding of cancer biology, multiomics technologies, and precision medicine.

Key Responsibilities:

1. Multiomics Data Analysis & Integration

• Analyze large-scale multiomics datasets, including proteomics, lipidomics, transcriptomics, spatial omics, and clinical data.
• Develop and optimize computational pipelines for data preprocessing, normalization, quality control, and statistical analysis.
• Integrate heterogeneous molecular and clinical datasets to identify biological signatures associated with treatment response and resistance.
• Perform differential expression/abundance analysis, pathway enrichment, clustering, dimensionality reduction, and biomarker discovery.
• Analyze spatially resolved molecular data, including mass spectrometry imaging (MSI), and integrate spatial information with other omics layers.

2. Artificial Intelligence & Machine Learning

• Design, develop, train, and validate AI/ML models for predicting cancer patients' responses to immunotherapies and other targeted treatments.
• Apply supervised and unsupervised machine learning techniques to high-dimensional biological datasets.
• Explore advanced approaches such as deep learning, multimodal data fusion, and explainable AI.
• Perform feature selection, model optimization, cross‑validation, and independent validation to ensure robust and reproducible results.
• Translate computational findings into biologically meaningful and clinically relevant insights.

3. Bioinformatics Tools & Computational Pipeline Development

• Develop, implement, and maintain reproducible bioinformatics workflows using Python, R, and relevant computational tools.
• Apply established bioinformatics packages and frameworks for proteomics, transcriptomics, and spatial multiomics analysis.
• Work with AI/ML libraries such as Scikit‑learn, PyTorch, TensorFlow, or equivalent frameworks.
• Manage complex biological datasets and contribute to building structured, scalable multiomics databases.
• Ensure data quality, traceability, documentation, and reproducibility across computational workflows.

4. Precision Oncology & Biomarker Discovery

• Collaborate with the scientific team to identify and validate molecular biomarkers associated with treatment response and resistance.
• Interpret computational results in the context of cancer biology, tum