Senior Project Scientist (Permanent)

JR France; Paris; À distance; EUR 70 000 - 100 000; Plein temps

Résumé du poste

A leading company in drug discovery is seeking a Senior Project Scientist in Paris to develop cutting-edge AI methods for target identification and drug repurposing. This role involves leading an AI team, conducting interdisciplinary collaboration, and leveraging deep learning techniques to enhance drug discovery processes. The ideal candidate will have a Ph.D. in a relevant field and a strong track record in computational biology.

Qualifications

• Experience leading a multidisciplinary AI team.
• Proven track record designing and deploying deep learning models.
• Strong expertise in integrating multi-omics data.

Responsabilités

• Develop method for target identification and drug repurposing.
• Lead a multidisciplinary AI team and set project goals.
• Collaborate with biologists and engineers to convert findings into insights.

Connaissances

Deep Learning

Systems Biology

Interdisciplinary Collaboration

Computational Biology

Effective Communication

Formation

Ph.D. in Computational Biology, Bioinformatics, Systems Biology, or related field

Description du poste

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Senior Project Scientist (Permanent), paris

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Client:

Next Phase Recruitment

Location:

paris, France

Job Category:

Other

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EU work permit required:

Yes

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Job Reference:

252085822462676172832761

Job Views:

3

Posted:

09.06.2025

Expiry Date:

24.07.2025

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Job Description:

My client are seeking a Senior Drug Discovery Scientist with a strong background in deep learning and systems biology to develop SOTA methods for target identification and drug repurposing. You will develop large scale causal models of the cells to address the exciting challenge of predicting cells response to perturbations, and identify the optimal treatment given a disease. You will lead an AI team to convert ideas into models and eventually actionable therapeutic insights. The main office based in France and offers full remote working.Responsibilities:Method Development for Target Identification and Drug Repurposing: Develop SOTA large scale causal models on omics data, to learn cell response to perturbations and predict the optimal target and drugs to address a given disease.Lead an AI Team: Lead a multidisciplinary AI team by mentoring scientists and engineers, setting clear project goals, and fostering a culture of innovation and collaboration across computational and experimental disciplines.Interdisciplinary Collaboration: Work closely with biologists, engineer and stake holders to translate computational findings into actionable drug discovery insights.Continuous Learning and Innovation: Stay abreast of the latest advancements in computational biology, deep learning, and systems biology, continuously refining your methods and incorporating new technologies.Effective Communication: Present complex data and concepts clearly to both scientific and non-scientific audiences, including key stakeholders in pharmaceutical companies.Requirements:Ph.D. in Computational Biology, Bioinformatics, Systems Biology, or a related field.Expertise in Deep Learning for Target Identification or Drug Repurposing: Proven track record in designing and deploying deep learning models (including generative, Bayesian, and causal models) applied to omics data to uncover novel drug targets.Network based Drug Repurposing Expertise: Demonstrated ability to apply network-based approaches to target identification and drug repurposing, utilising network medicine techniques to map and analyse complex biological interactions.Systems Biology Proficiency: Expertise in integrating multi-omics data and modelling biological systems to derive actionable insights.Single-Cell Analysis Experience: Extensive experience in computational biology with a focus on single-cell analysis to capture cellular heterogeneity.Interdisciplinary Team Player: Proven ability to work effectively within cross-functional teams and communicate complex concepts to diverse audiences.