Senior Drug Discovery Scientist (Remote)

SLS Services Limited; France; À distance; EUR 80 000 - 100 000; Plein temps

Résumé du poste

A leading drug discovery firm in France is seeking a Senior Drug Discovery Scientist to develop state-of-the-art methods for target identification and drug repurposing. The candidate will lead an AI team, collaborate with interdisciplinary teams, and communicate insights effectively. A Ph.D. in a relevant field and expertise in deep learning are essential. This position offers full remote working options.

Qualifications

• Ph.D. in Computational Biology, Bioinformatics, or Systems Biology.
• Expertise in designing and deploying deep learning models on omics data.
• Demonstrated ability in network-based drug repurposing techniques.

Responsabilités

• Develop SOTA models to learn cell response and predict optimal treatments.
• Lead a multidisciplinary AI team and set clear project goals.
• Collaborate closely with biologists and engineers for actionable insights.

Connaissances

Deep Learning for Target Identification

Systems Biology

Network Medicine Techniques

Single-Cell Analysis

Interdisciplinary Collaboration

Formation

Ph.D. in Computational Biology or related field

Description du poste

We 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.