Job Description

About Us

Under the Apple Tree Partners (ATP) portfolio,  Deep Apple Therapeutics is a Bay Area biotechnology company with a focus on combining capabilities in molecular docking and structural biology to create a nucleus for accelerated drug discovery through advanced computer-aided drug design technologies. Deep Apple Therapeutics is applying a state-of-the-art technology research platform based on advanced computational modeling and large-scale compound docking (LSD), cryo-EM-based structural biology, and deep learning to drug discovery.

Role Description

We are seeking an experienced and visionary leader to serve as the Head of Computational Chemistry and lead our computational efforts in virtual hit discovery. Reporting directly to the Head of Drug Discovery, you will oversee a team of computational chemists, data scientists, and machine learning engineers to integrate deep learning models into our drug discovery pipeline. This role is pivotal in advancing our virtual screening capabilities, optimizing molecular design, and collaborating cross-functionally to translate computational insights into viable therapeutic leads. The ideal candidate brings over 10 years of expertise in computational modeling, with knowledge on deep learning applications for drug discovery.

Key Responsibilities

• Lead and mentor a multidisciplinary team in the design, implementation, and optimization of computational chemistry workflows for virtual hit discovery, including ligand-based and structure-based modeling. 
• Develop and deploy deep learning models (generative AI for molecule design) to predict molecular properties, binding affinities, and ADMET profiles. 
• Oversee the integration of high-throughput virtual screening platforms, utilizing large-scale datasets and cloud-based computing resources (AWS and Google Cloud). 
• Collaborate with biology, medicinal chemistry, and machine learning teams to validate computational predictions through iterative feedback loops. 
• Drive strategic initiatives, including partnerships with academic institutions, tech companies, and CROs to enhance our AI-driven discovery capabilities. 
• Stay abreast of emerging technologies in computational chemistry and deep learning, incorporating them into our pipeline to maintain a competitive edge. 
• Manage project timelines, budgets, and resources while ensuring compliance with data integrity and intellectual property standards. 

Required Qualifications and Skills

• PhD in Computational Chemistry, Cheminformatics, Bioinformatics, or a related field. 
• Minimum of 10 years of professional experience in computational modeling within the biotech or pharmaceutical industry, with at least 5 years in a leadership role. 
• Proven experience in deep learning frameworks applied to molecular modeling, including experience with generative models, reinforcement learning, or multimodal AI for drug discovery. 
• Strong track record in virtual hit discovery leading to drug candidates.
• Demonstrated success in leading teams to deliver computational insights that have advanced drug candidates from hit identification to lead optimization. 
• Proficiency in programming languages such as Python, with experience in data analysis, machine learning pipelines, and high-performance computing. 
• Excellent communication skills, with the ability to translate complex technical concepts to non-experts.

Job Tags

Similar Jobs