Offers “Station F”

New Station F

Computational Biologist – Customer facing

  • CDD
  • Paris (Paris)

Job description

About

Scienta Lab is a deeptech company harnessing artificial intelligence to transform the drug discovery and development process in immunology and inflammation.
With its unique and proprietary EVA foundation model dedicated to immune-mediated diseases, Scienta Lab leverages multimodal data to bridge the gap of translational research, accelerate the validation of new therapeutic targets and the development of personalized treatments. The company’s research activities, led in partnership with top-tier academic institutions across Europe, are regularly featured in medical journals and international congresses.
Scienta Lab is based in Biolabs Hôtel Dieu and has been selected amongst the 2023 edition of the Future 40 program which rewards the most promising startups of Station F each year. In December 2023, the company announced a seed round of 4M from CentraleSupélec Venture and a team of world-class business angels and is thus seeking for top talents to accelerate its development.

We are a team with diverse backgrounds in AI, Computational Biology, Immunology and pharma industry, with half the company with PhDs. Join us and be a part of our exciting journey to unravel the mysteries of the immune system!

Discover who we are and what we value here .

Job Description

As customer-facing Computational Biologist at Scienta Lab, you will serve as the scientific bridge between our cutting-edge AI platform and our pharmaceutical and biotech partners. You will lead RNAseq and transcriptomics analyses using our EVA foundation model, translating complex computational insights into actionable biological understanding for our clients. Your role combines deep scientific expertise with client relationship management to drive adoption and success of our AI-driven solutions, and make sure we address accurately our customer scientific questions.

We value high-level coding and research and aim to develop a culture of continuous improvement in the team. We implement good practices to deliver production-ready software and top-tier scientific publications in these areas. This position offers excellent mentorship and growth opportunities.

Main Missions :

· 
Leverage Scienta Lab’s foundation model EVA to answer biopharma scientific questions by providing key insights on immune-mediated diseases mechanisms, and drug mechanisms of actions. Design and execute comprehensive analyses leveraging tools at your disposal.

· 
Translate complex computational results into clear, actionable biological interpretations tailored to each client's therapeutic areas and research objectives

· 
Participate in client meetings, proposal development, and proof-of-concept studies to demonstrate our models’ capabilities and scientific value

Preferred Experience

Who we are looking for

· 
Degree (Master's or PhD) in Computational Biology, Bioinformatics, Immunology, or related field

· 
Extensive experience with RNAseq data analysis including quality control, differential expression, and adequate processing and visualization

· 
Solid software engineering skills including Python proficiency, version control (Git), testing, and CI/CD practices

· 
Strong expertise in transcriptomics tools and workflows (DESeq2, edgeR, GSEA, Seurat, Scanpy, CellRanger)

· 
Excellent communication skills for presenting complex scientific concepts to diverse audiences

· 
Professional working proficiency in English

How to stand out

· 
You have high agency, look for solutions rather than problems and you are a team-player willing to go beyond your job description

· 
Experience in pharmaceutical or biotech industry, particularly in client-facing roles

· 
You are experienced in working in dynamic and changing environments such as startups

· 
Familiarity with immunology and inflammation biology and ability to interpret transcriptomic data in biological context

Additional Information

·  Contract Type: Full-Time
·  Location: Paris
·  Occasional remote authorized

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