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About the Role

The Omics Data Scientist will build omics processing pipelines to extract signals from multiple modalities (whole genome sequencing, transcriptomics, and proteomics), ensuring experimental reproducibility, data standardization, and correction of technical biases. You will extract relevant features, deliver AI-ready omics data, establish mono-modal baselines, reproduce state-of-the-art results, and contribute to a multimodal architecture.

Responsibilities

Design pipelines for whole genome sequence, transcriptomics and proteomics normalization, denoising, standardization and feature engineering.
Benchmark omics based AMR prediction from the literature as well as omics baselines.
Develop and implement deep learning models (transformers, graph neural networks, autoencoders) for multi-OMICs integration supporting predictive modeling and mechanistic interpretation.
Adapt and implement computational biology approaches for translational diagnostic applications.
Collaborate closely with microbiologists, computer vision experts, and optical physicists to ensure biological interpretability of AI models.
Contribute to scientific publications, conferences, and intellectual property (patents) highlighting novel insights from integrated OMICs and optical data.

Requirements

Engineer degree, Master's degree, or PhD in computational biology or machine learning applied to Omics.
A minimum of 2 years of proven hands-on omics processing and omics-based deep learning model training.
Proficient in python, comfortable leveraging omics processing software, documents systematically, uses continuous integration tools and best coding practices.
Able to organise their working day independently once roadmaps are established, anticipate scheduling constraints (computation time, data availability), check for spurious correlation and deliver statistically meaningful conclusions.
Comfortable contributing across tasks in a small laboratory environment.
Clear written and verbal scientific communication in English.

Skills

Omics processing
Omics-based deep learning model training
Python
Deep learning models (transformers, graph neural networks, autoencoders)
Multi-OMICs integration
Computational biology approaches
Scientific communication

Location

Paris

Work Type

Flexible remote
Permanent position (CDI)

Experience Level

Minimum of 2 years of proven hands-on omics processing and omics-based deep learning model training

Education Level

Engineer degree
Master's degree
PhD in computational biology or machine learning applied to Omics

Benefits

Budget for remote work equipment
Gymlib subscription
Premium health insurance (Alan in France)
Swile card for meals (if based in France)
Frequent team events and in-person gatherings every quarter

About the Company

Spore.Bio is a deeptech startup founded in 2023 that is redefining microbiological quality control in pharmaceutical, food & beverage, and cosmetics manufacturing.
Spore.labs deploys biophotonic and deep-learning technology on factory floors and takes Spore.Bio's core technology into new territory: from AMR detection to microbiome research and beyond.