Assistant Principal Scientist – Cheminformatics (Hybrid)

at  Insmed EU Careers

Company Description:
Insmed is a global biopharmaceutical company on a mission to transform the lives of patients living with serious and rare diseases. Our most valuable resource is our employees, and everything we do is motivated by a patients-first mentality. We are dedicated to growing our team with talented individuals from around the world who are willing to challenge the status quo, solve problems, and work collaboratively with a sense of urgency and compassion.
Guided by our core values of collaboration, accountability, passion, respect, and integrity, we aim to foster an inclusive, diverse, and flexible work environment, where our employees are recognized for leaning in and rolling up their sleeves. If you share our vision and want to work with the most dedicated people in the biopharma industry, come to Insmed to accelerate your career.
Recognitions:

A CERTIFIED GREAT PLACE TO WORK

We believe our company is truly special, and our employees agree. In July 2024, we became Great Place to Work-certified in the U.S. for the fourth year in a row. We are also honored to have been listed on the Best Workplaces in Biopharma™, Best Workplaces in New York™, and Best Workplaces for Millennials™ lists.
Summary:
We are looking for an innovative Cheminformatician with a background in computational chemistry who is passionate about the transformative power of data engineering, modeling, and ML/AI in drug discovery. In this role, you will work closely with our team of chemists, computational chemists, and data scientists, playing a critical part in developing Insmed Innovation’s discovery design platform. This platform will leverage cutting-edge tools, data-driven methodologies, and machine learning to accelerate our drug discovery efforts. An exciting aspect of this position is the opportunity to collaborate with our AI group, implement and explore new methods and technologies that will revolutionize and enhance our drug design capabilities. This role offers an exciting opportunity to join and build a new team and be at the forefront of integrating advanced technologies into drug discovery, leveraging your expertise to make a tangible impact.
Responsibilities:

The role will focus on deploying, developing, and integrating cutting-edge tools, managing bioactivity databases, generating machine learning models, and collaborating with our broader data science and informatics team. Your work will enable broad access to these tools via APIs, supporting our designers on therapeutic development projects across various modalities from small molecules to more novel ones like oligonucleotides. By applying a broad set of computational chemistry and cheminformatics approaches, you will play a crucial role in advancing data-driven molecular design and medicinal chemistry efforts. Your contributions will have a significant impact across our global team. You will be responsible for, among other things:

• Deploying cheminformatics tools, workflows, and models to extract, integrate, analyze, and visualize complex chemical, structural, pharmacological, and ADMET data within the context of structure-based drug discovery.
• Playing an active role in assessing and deploying new computational chemistry tools through external collaborations.
• Exploring the application of AI-driven molecular design and generative approaches, including active learning.
• Curating and preparing datasets—including chemical data warehouses and data marts—to enable better data access, analysis, and modeling across our team.
• Engaging with technologies for data mining and virtual screening of ultra-large databases.
• Working closely with cross-functional teams, including biology, pharmacology, and ADME, to help identify opportunities for building datasets and models that will impact ongoing projects.
• Exploring new modalities, including using cheminformatics to help describe oligonucleotide chemical space to enable rational discovery.
• Identifying opportunities to publish in peer-reviewed journals to communicate any new insights, methods, or results to the scientific community.

Position Requirements (Required and/or Preferred Skills, Experience and Education):Required: Skills and Experience:

• Ph.D. or equivalent experience in cheminformatics, computational chemistry, or a related discipline.
• Experience using cheminformatics toolkits or computational chemistry tools to solve problems such as: Similarity searching, Matched pair analysis, Clustering, QSAR modelling, Analysis and visualisation of structure-activity relationships, Virtual library enumeration
• Strong coding skills in Python or other scripting language, experience in using KNIME or Pipeline Pilot and familiarity with common data science packages.
• Familiarity with SQL, querying of relational databases, and use of ETLs and APIs.
• Advanced analytical and critical problem-solving skills, combined with scientific creativity and attention to detail.
• Good interpersonal, oral, and written communication skills: track record of peer reviewed publications, patents or conference papers

Desirable:

• Proficient in using in silico tools within collaborative, multidisciplinary medicinal chemistry research.
• Strong foundation in molecular recognition and the structural/physicochemical determinants of small molecule-protein binding.
• Experienced with ELNs, LIMS, including Dotmatics, ActivityBase, or similar systems.
• Skilled in using GitHub, Slurm, Docker, and cloud platforms like Google Cloud, AWS, or Azure.
• Knowledgeable in AI techniques, particularly Deep Generative Models.

Travel Requirements:
N/A
Compensation & Benefits:
We’re committed to investing in every team member’s total well-being, now and in the future. We offer a competitive total-rewards package to all employees around the world.
Additional Information:
Insmed Incorporated is an Equal Opportunity/Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law.
Unsolicited resumes from agencies should not be forwarded to Insmed. Insmed will not be responsible for any fees arising from the use of resumes through this source. Insmed will only pay a fee to agencies if a formal agreement between Insmed and the agency has been established. The Human Resources department is responsible for all recruitment activities; please contact us directly to be considered for a formal agreement.
Applications are accepted for 5 calendar days from the date posted or until the position is fille

• Deploying cheminformatics tools, workflows, and models to extract, integrate, analyze, and visualize complex chemical, structural, pharmacological, and ADMET data within the context of structure-based drug discovery.
• Playing an active role in assessing and deploying new computational chemistry tools through external collaborations.
• Exploring the application of AI-driven molecular design and generative approaches, including active learning.
• Curating and preparing datasets—including chemical data warehouses and data marts—to enable better data access, analysis, and modeling across our team.
• Engaging with technologies for data mining and virtual screening of ultra-large databases.
• Working closely with cross-functional teams, including biology, pharmacology, and ADME, to help identify opportunities for building datasets and models that will impact ongoing projects.
• Exploring new modalities, including using cheminformatics to help describe oligonucleotide chemical space to enable rational discovery.
• Identifying opportunities to publish in peer-reviewed journals to communicate any new insights, methods, or results to the scientific community