About Us

Odyssey Therapeutics is propelling drug development beyond what is now possible to deliver medicines that address critical needs of patients with inflammatory diseases and cancer. We achieve unprecedented speed and efficiency by bringing together a target-centric approach, a toolbox of cutting-edge technologies, and a team of accomplished, world-class drug hunters. By reimagining the drug development process, we are creating a deep and broad drug pipeline that holds the potential to transform human health.

Position Details

Job Title: Associate Director, Generative Modeling Chemist
Location: Boston, MA
Employment Type: Full-Time
Department: Data Science and Research Informatics

The Opportunity

We are seeking a Generative Modelling Chemist to join our innovative team. This role involves designing molecules for various projects, setting up and conducting generative runs, and supporting project chemists. As a thought partner with medicinal chemistry, computational chemistry, and informatics teams, you will play a critical role in driving our drug discovery efforts.

Key Responsibilities

• Design and Innovation: Design molecules for projects by applying generative modelling techniques, ensuring the maximization of structure-activity learning in each compound design.
• Collaborative Development: Partner with medicinal chemists, computational chemists, and informatics teams to develop new hypotheses and advance project objectives.
• Platform Development: Contribute to the continuous development and enhancement of the generative modelling platform, making it a catalyst for innovation within the company.
• Support and Training: Support training and promotion of the generative platform internally and with partners, acting as a guide to other scientists aspiring to be effective users of the platform.
• Data Integration: Ensure the integration of generative design outputs with broader data initiatives, facilitating seamless communication and project advancement.
• Innovative Algorithm Development: Engage in the development of new generative algorithms tailored for specific drug discovery challenges, ensuring the platform stays at the cutting edge of technology.
• Continuous Learning and Development: Stay updated with the latest advancements in AI, machine learning, and computational chemistry. Regularly participate in workshops, seminars, and courses to continuously improve and share knowledge with the team.
• Collaborations and Partnerships: Facilitate collaborations with academic institutions, industry partners, and consortia to leverage external expertise and resources, thereby enhancing the internal capabilities of the organization.
• Impact on Pipeline and Portfolio: Articulate the impact of generative design efforts on the drug discovery pipeline, highlighting successes and strategically planning future directions to align with organizational goals.

About You

• Doctorate in computational chemistry, medicinal chemistry, cheminformatics, computational biology, or a related field; individuals with lab-based backgrounds and strong computational experience are encouraged to apply.
• 3+ years of industry experience in pharma/biotech within a multidisciplinary drug discovery team.
• In-depth knowledge of medicinal/computational chemistry, principles of ligand and structure-based design, DMPK principles, multi-parameter optimization, and a solid understanding of biology and synthetic chemistry.
• Basic understanding of physics-based modelling and simulation.
• Basic understanding of machine learning applied in predictive modelling, deep learning, and its application in generative design.
• Experience using Schrodinger suite, Knime or equivalent, Spotfire/Vortex or equivalent.
• Familiarity with working in high-performance computing environments, including Linux and scripting.
• Strong communication and organizational skills, with the ability to collaborate effectively across different teams.
• Enthusiastic problem solver with the ability to multitask effectively.

Desirable

• Experience in machine learning and deep learning (development, maintenance, deployment of models using tools such as PyTorch, TensorFlow, scikit-learn).
• Basic experience in scientific programming (Python, bash scripting, SQL).
• Experience working with remote engineering teams and third-party contractors.
• Relevant publication track record.

Value Delivered

• Maximizing Learning: Enhance structure-activity learning in compound designs, driving forward our understanding and capabilities in drug development.
• Hypothesis Development: Serve as a catalyst for developing new hypotheses that push the boundaries of our research projects.
• Mentorship: Guide and mentor other scientists in effectively utilizing generative chemistry platforms, fostering a culture of continuous learning and innovation.