Staff Scientist, Machine Learning and Cheminformatics
Atomwise
This job is no longer accepting applications
See open jobs at Atomwise.See open jobs similar to "Staff Scientist, Machine Learning and Cheminformatics" University of Toronto Entrepreneurship.Atomwise is a TechBio company leveraging AI/ML to revolutionize small molecule drug discovery. The Atomwise team invented the use of deep learning for structure-based drug design; a core technology of Atomwise’s best-in-class AI discovery and optimization engine, which is differentiated by its ability to find and optimize novel chemical matter. The company’s belief is that structurally novel chemical matter increases the likelihood of developing first-in-class and best-in-class medicines that have the potential to transform patient care.
Atomwise has extensively tested its discovery and optimization engine, delivering hit ID success in over 230 academic and collaboration projects-to-date that cover a wide breadth of protein classes and numerous “hard-to-drug” targets. Atomwise is building a wholly-owned pipeline of small molecule drug candidates and plans to file an IND application this year for its lead candidate, a novel allosteric TYK2 inhibitor with first-in-class and best-in-class potential.
The company has raised over $174 million from leading venture capital firms to advance its vision to invent a better way to discover and develop new medicines to help patients.
About the role
Our nimble Machine Learning, Cheminformatics, and Research team is responsible for the research and development of our drug discovery platform. You will conduct research in developing and benchmarking machine learning models for early-stage drug discovery. You will collaborate extensively with machine learning engineers and fellow cheminformatics researchers to build models with top-tier performance. We believe in dogfooding; internal program support is an integral part of the role.
Key Responsibilities
- Design, develop, train, and benchmark large generative and predictive models for bioactivity prediction and chemical design, in collaboration with our machine learning team
- Develop and maintain data pipelines for processing large-scale datasets in cheminformatics and structural biology
- Develop methods, datasets, and tools for benchmarking and validation of ML models
- Collaborate with CADD scientists, medicinal chemists, biologists, and other cross-functional roles within project teams to support and facilitate platform application to specific projects
- Communicate cross-functionally with a wide range of company stakeholders
- Contribute to our codebase with well-designed and readable Python code
- Contribute to a collaborative and inclusive team culture
Required Qualifications
- Ph.D in Computer Science, Statistics, Cheminformatics, Bioinformatics, Computational Biology, or a related discipline
- 5+ years experience in methods and algorithm development leveraging biochemical data
- Experience working with large-scale datasets, performing efficient data curation, and working effectively with datasets that are complicated, messy, or incomplete
- Experience in virtual screening, QSAR, molecular docking, pharmacophore modeling, or other molecular modeling modalities
- Sound knowledge of statistics, data analytics, and data visualization
- Strong coding skills in at least one high-level programming language (Python, R, Java, C++, etc) and cheminformatics toolkits (e.g., RDKit, DeepChem, etc)
- Strong familiarity with Linux command-line environment
- Proactive team player, effective communicator, and creative problem solver
Preferred Qualifications
- Experience in implementing and applying modern deep learning algorithms and frameworks (e.g., scikit-learn, PyTorch, PyG, etc.)
- Familiarity with standard public databases relevant to protein-ligand binding affinity, ADMET properties, and protein-protein interactions
- Record of successful mentorship of junior scientists and effective cross-functional communication
- Record of publications and conference presentations relevant to AI in drug discovery
- Experience with cloud computing environments (AWS/Azure/GCE)
Compensation & Benefits
- Competitive salary, commensurate with experience
- Stock compensation plan – you’ll be an Atomwise co-owner
- Platinum health, dental, and vision benefits for you and your dependents
- 401(k) retirement plan with generous company match (up to 4%)
- Flexible paid time off (PTO), 13 paid holidays, and wellness breaks for employees to spend time with their loved ones and recharge
- Health Savings and Flexible Spending Account options to help save money on healthcare, daycare, and commuting
- Employee Assistance Program (EAP) and Pet Insurance
- Funding for professional development and conference attendance
- Flexible work schedule
- Generous paid parental leave
Atomwise is an equal opportunity employer and strives to foster an inclusive workplace. We are a TechBio company leveraging AI/ML to revolutionize small-molecule drug discovery, and we know that we need a diverse team to develop medicines that serve diverse populations. Accordingly, Atomwise does not make any employment decisions (including but not limited to, hiring, compensation, and promotions) on the basis of race, religion, color, national origin, gender, gender identity, sexual orientation, age, veteran status, disability status, or any other characteristics protected by applicable federal, state, and local law.
We strongly encourage people of diverse backgrounds and perspectives to apply.
Pay range for this role is between $210,000 - $250,000. Actual compensation packages are determined by several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, certifications, relevant education or training, and specific work location.
This job is no longer accepting applications
See open jobs at Atomwise.See open jobs similar to "Staff Scientist, Machine Learning and Cheminformatics" University of Toronto Entrepreneurship.