Senior Drug Discovery Scientist

Job title:

Senior Drug Discovery Scientist

Company:

DeepLife

Job description

We are seeking a Senior Drug Discovery Scientist with a strong expertise 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. Your will lead an AI team to convert ideas into models and eventually actionable therapeutic insights.Tasks

• 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.

RequirementsQualifications (Ranked by Importance):

• 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.

BenefitsWhy Join DeepLife?At DeepLife, you’ll play a pivotal role in bridging the gap between computational innovation and practical drug discovery. Our team is composed of 90% PhD, 15+ nationalities across EU and US, fostering a unique research environment for this project.If your DNA is also Ambitious, Creative, Tolerant and Goal-oriented, apply today and join us to make a difference!DeepLifeDeepLife is a series A startup focused on addressing the urgent need to increase drug discovery reliability by acting on the earliest step, drug target identification. This consists of identifying, a molecular target, such as a protein, that will trigger the transition from disease to healthy cells. With current methods, only 1 target in 10,000 reach the market, leading to a significant loss of time and efforts in the community.Our approach is to leverage the recent revolution in the omics data, measuring precisely cells activity at large scale, and build foundation models to mimic cell behavior in various contexts and identify the optimal trigger to reverse disease state.We offer a research friendly environment, with 90% of the company holding a PhD, with academic collaborations and publications. The team is international and composed of +10 different nationalities. The company is remote first with most of the work is remote and regular events organized in our offices in Paris.

Expected salary

Location

Paris

Job date

Wed, 02 Apr 2025 22:12:42 GMT

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