Deep Learning Scientist — OMICs & AMR

About us

At Spore.Bio, we’re reinventing how microbiology is done in industrial and clinical settings. After months spent inside factories and labs, we saw firsthand how slow and constrained traditional microbiological workflows still are. So we built a new paradigm using advanced optics and deep learning to deliver results in seconds instead of days.

Today, we’re taking this mission a step further.

We created Spore.Labs, our fundamental research division dedicated to one of the biggest global health challenges starting with antimicrobial resistance (AMR). With the support of the Google.org AI for Science Initiative, Spore.Labs is launching an open-source program to reduce AMR diagnostic time from days to minutes enabling rapid identification of resistance genes and promoting targeted, responsible antibiotic use.

And now, we’re entering the next chapter.

We’re building a team of exceptional researchers, engineers, and scientists who will bring this project out of stealth mode and push the boundaries of biophotonics, genomics, and AI. If you want to work at the frontier of AMR research, help shape open scientific infrastructure, and contribute to a global effort backed by Google, we’d love to meet you.

About the role

As a Deep Learning Scientist specializing in OMICs, you will design computational frameworks to analyze and integrate proteomic, transcriptomic, and genomic data with optical and biological measurements.

Your work will focus on proteomics to identify molecular signatures underlying resistance, while genomic information will complement analyses for deeper mechanistic insights.

Main Responsibilities

• Develop and implement deep learning models (transformers, graph neural networks, autoencoders) for multi-OMICs integration, with primary focus on proteomics.

• Design pipelines for mass spectrometry–based proteomics data processing: feature extraction, normalization, quantification, and denoising.

• Integrate transcriptomic and genomic datasets to support predictive modeling and mechanistic interpretation.

• Combine molecular OMICs profiles with optical and microbiological data to model resistance mechanisms and predict phenotypic outcomes.

• Adapt and implement state-of-the-art deep learning approaches from computational biology 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.

• Building our team to expand and strengthen our expertise in OMICs.

• Strongly contribute to our clinical strategy and product development roadmap.

About you

Required qualifications/ experience :

We value curiosity, initiative, and a growth mindset: not every box needs to be ticked to apply.

• Strong deep learning expertise, including transformers, GNNs, autoencoders, or self-supervised models.

• PhD +4 years of experience in ML for OMICs.

• Proven experience with proteomics data (mass spectrometry, feature extraction, normalization, integration).

• Experience with transcriptomic and genomic datasets (secondary focus) and multi-OMICs integration.

• Familiarity with Python, PyTorch, and data preprocessing/analysis pipelines.

• Knowledge of reproducible coding practices and version control.

Why joining us?

• Work in an innovative and rapidly growing startup.

• Participate in exciting and impactful projects.

• Evolve in a collaborative and stimulating work environment.

• Opportunities for professional development and continuous training.

What we offer

We believe that flexibility and trust are important parts of a company. Our work environment reflects this thanks to:

• Flexible remote: If you live in Paris, you can work from our office or from your place with no constraints.

On top of that, we offer many perks such as:

• a budget for remote work equipment

• a Gymlib subscription for you to stay in shape wherever you are

• premium health insurance (Alan in France)

• a Swile card for your meals, if you are based in France

• frequent team events and in-person gatherings every quarter!

Recruitment process

• 30-min call with the Hiring Manager

• 45-min personality interview with two team members

• A 1 hour technical case study followed by a debrief with team members

• 1 hour Founders interview

• Reference calls

You might also be invited to meet other team members at the office for a lab visit and a coffee !

This is a unique opportunity for someone who thrives on curiosity and has a genuine passion for technology. If you enjoy taking on challenges and solving complex problems, this role will provide the perfect environment for growth and impact. The ideal candidate is someone who is self-driven, eager to learn, and excited to contribute to shaping the future of microbiology monitoring. Join our innovative and dynamic team, and let's make a difference together! We look forward to meeting you!