Computational Medicinal Chemist

Novartis Group Companies; San Diego (CA); Hybrid; USD 126,000 - 257,400; Full time

Job summary

Novartis Group of Companies in San Diego, CA, is seeking a Senior Expert I/II, Data Science to advance computational drug discovery using ML, SAR, and physics-based CADD. You will collaborate with scientists to craft inventive solutions for drug targets and lead optimization across multiple modalities.

The role emphasizes predictive modeling, lead characterization and screening, and cross-disciplinary work in a hybrid setting with competitive compensation and US benefits.

Qualifications

• PhD in medicinal chemistry, computational chemistry, computational biology, or related field; MS with pharma/biotech experience considered.
• 3+ years in a drug discovery environment with project teams.
• Strong publication history and familiarity with computational drug design tools.

Responsibilities

• Design medicinal chemistry efforts using SAR, structure-based and ligand-based design, and PK/PD concepts.
• Apply machine learning, active learning, and physics-based CADD for small molecule discovery.
• Collaborate with interdisciplinary teams to drive lead identification and optimization.
• Develop predictive models from high-content and time-resolved screening data, including imaging.

Skills

Machine learning

Team collaboration

Data visualization

Python

Education

PhD in medicinal chemistry or related field

MS with pharma/biotech experience

Tools

Schrödinger

OpenEye

CCG

Job description

Job Description Summary

Join our vibrant and innovative Computer-Aided Drug Discovery (CADD) team in California, where we bring together diverse talents to redefine the way Biomedical Research discovery teams validate and develop new targets. We are a driving force behind drug discovery, and we are now eagerly searching for an exceptional computational scientist like you to join our ranks.

Imagine the opportunity to unlock hidden knowledge and disruptive insights from the vast and invaluable data collected by one of the world's most renowned pharmaceutical companies. We need your expertise, experience, and unwavering passion to help us extract this wealth of information. Collaborating with a multidisciplinary group of scientists, you will be at the forefront of crafting inventive solutions to the most pressing drug discovery challenges, forging new paths toward groundbreaking medicines.

Are you ready to seize this extraordinary chance to make a significant impact in the field of drug discovery? We invite you to embark on this thrilling journey with us, as we push the boundaries of what's possible in scientific exploration. Join our team and be part of a revolution that will shape the future of medicine.

Together, we will transform the landscape of drug discovery, accelerate breakthroughs, and change lives.

Job Description

Internal Job Title: Senior Expert I/II, Data Science

Position Location: San Diego, CA, hybrid

Your Responsibilities Include

• Drive the design of medicinal chemistry efforts by applying in-depth knowledge of structure-activity relationships (SAR), structure-based and ligand-based drug design, a profound understanding of target biology, and predictive methods for assessing on- and off-target activity, physical properties, pharmacokinetics/pharmacodynamics (PK/PD), and synthetic feasibility.

• Thrive at the intersection of experimental and groundbreaking digital technologies, with a particular emphasis on expertise in machine learning, active learning and physics-based CADD methodologies as applied to small molecule drug discovery as well as in the induced proximity space.

• Stay abreast of scientific literature and engage with internal and external scientists to incorporate biological insights into lead characterization and screening initiatives.

• Collaborate with interdisciplinary project teams to facilitate effective decision-making throughout the target identification, lead optimization and drug candidate nomination process. This involves applying and developing predictive models based on high-content and time-resolved screening data, including imaging techniques.

• Drive hypothesis generation to enhance clinical success rates for programs involving small molecules, peptides, RNAs, protein degradation, molecular glues, transient covalent inhibitors, and kinetic stabilization of drug-target complexes.

• Take a leading role in cross-disciplinary mechanistic studies using physics-based modeling and simulation, biophysical characterization, and cellular validation. These studies will inform the strategic targeting strategies of discovery projects, aiming for optimal mechanisms of action (MoAs).

Essential Requirements

• PhD in medicinal chemistry, computational chemistry, computational biology, computational chemical biology, or a related field. Candidates with a laboratory-based background in chemistry and biology, supplemented with strong computational experience, are also encouraged to apply. We will also consider MS applicants with 6+ years of relevant Pharma/biotech experience.

• 3+ years of experience working with project teams in a drug discovery environment.

• Proven track record of innovation through analogue design, leading to significant impact on discovery projects.

• Familiarity with computational drug design tools (e.g. Schrdoinger, CCG, OpenEye, etc.), high-performance computing environments, and strong publication history in peer-reviewed journals.

• Proactively anticipates project needs with a clinical focus.

• Demonstrates rigor and diligence in idea substantiation, analogue design, and experimentation.

• Strong team orientation with multitasking and adaptability in support and leadership roles.

• Effective listener with excellent written and oral communication skills.

• Proficient in data visualization to effectively communicate insights.

Compensation & Benefits

The salary for this position is expected to range between $126,000 and $234,000 USD annually for Senior Expert I, Data Science, and $138,600 and $257,400 USD annually for Senior Expert II, Data Science. The final salary offered is determined based on factors like, but not limited to, relevant skills andexperience, and upon joining Novartis will be reviewed periodically. Novartis may change the publishedsalary range based on company and market factors.

• Your compensation will include a performance-based cash incentive and, depending on the level of therole, eligibility to be considered for annual equity awards.
• US-based eligible employees will receive a comprehensive benefits package that includes health, life anddisability benefits, a 401(k) with company contribution and match, and a variety of other benefits. Inaddition, employees are eligible for a generous time off package including vacation, personal days,holidays and other leaves.

EEO Statement

The Novartis Group of Companies are Equal Opportunity Employers. We do not discriminate in recruitment, hiring, training, promotion or other employment practices for reasons of race, color, religion, sex, national origin, age, sexual orientation, gender identity or expression, marital or veteran status, disability, or any other legally protected status.

Accessibility and reasonable accommodations

The Novartis Group of Companies are committed to working with and providing reasonable accommodation to individuals with disabilities. If, because of a medical condition or disability, you need a reasonable accommodation for any part of the application process, or to perform the essential functions of a position, please send an e-mail to [e-mail] or call [phone] and let us know the nature of your request and your contact information. Please include the job requisition number in your message.

Salary Range

$126,000.00 - $234,000.00

Skills Desired

• Artificial Intelligence (AI)
• Biostatistics
• Change Management
• Curious Mindset
• Data Governance
• Data Literacy
• Data Quality
• Data Science
• Data Visualization
• Deep Learning
• Graph Algorithms
• Learning Agility
• Machine Learning (ML)
• Machine Learning Algorithms
• Python (Programming Language)
• Stakeholder Engagement
• Statistical Analysis
• Time Series Analysis