About the Company:
VantAI combines cutting-edge machine learning with deep systems biology, physics and chemistry expertise to solve the most challenging problems in drug discovery. We specialize in the discovery of compounds and biologics that modulate complex protein-protein interactions, using data-driven modeling approaches. Our machine learning-powered in silico platform has helped leading biopharma partners advance their development programs at a fraction of the time and cost of traditional methods.
About the Role:
VantAI is seeking highly-motivated Computational Biologists interested in building the leading AI-enabled drug discovery platform for novel induced proximity therapeutic modality.
Successful candidates will work closely with the Computational Chemistry, Machine Learning and Application Engineering teams to tap into the wealth of evolutionary, structural and -omics data to unlock the full potential of unified machine learning representations and large-scale geometric deep learning generative models.
Projects may include designing large-scale scientific workflows for mining public and unique in-house data; developing novel systems biology and structural biology computational methods, tools and algorithms; and/or designing, training and fine-tuning best-in-class machine learning models. In our projects we apply induced proximity approaches to some of the most challenging targets considered “undruggable” as well as discover, build and develop novel proximity platforms spanning across multiple targets and disease areas.
We value individuals who want to make an impact, have a deep intellectual curiosity, enjoy solving challenging problems and have a track record of achievement. At VantAI, we believe that success is determined by talent and hard work, and individuals are given equal opportunities to grow and advance based on their abilities and contributions.
Key Responsibilities:
Develop pilot capabilities and create large-scale data pipelines from the ground up
Collaborate with other teams across VantAI and partnering organizations to achieve project goals by contributing code, analyses, benchmarks, optimizations and ideas to ongoing research-driven projects
Integrate biological insights into the next generation of AI/ML models for drug discovery
Validate and interpret computational predictions by working closely with experimentalists
Basic Qualifications:
Hold an MSc or PhD degree in computational biology, bioinformatics or a related field
Possess mixed academic and/or industrial experience, preferably in the biotech industry
Have a strong background in computational structural or systems biology
Demonstrate strong programming skills in Python, R and/or other languages
Experience building reproducible and scalable computational biology workflows
Experience designing and applying machine learning models
Preferred Qualifications:
Experience with geometric deep learning, graph neural networks, protein language models, transformers and representation learning is a plus
Preferably have prior exposure to drug discovery problems
Experience working with cloud-based infrastructure
Agile project management
NYC Salary: $120,000 - $180,000
This band is a reflection of the job description as written. Looking for a higher salary? Apply anyway! We are happy to speak to more experienced candidates who may require a higher salary and discuss that experience in our first touchpoint.
Top Skills
What We Do
VantAI pairs bleeding-edge machine learning techniques with deep systems biology expertise to build computational models that uncover hidden relationships between molecules, targets, and diseases. These models power a best-in-class solution that identifies and generates new molecular entities for targets of interest, repurposes existing molecules at any stage of development, uncovers accurate ADME and toxicological insights, and predicts adverse events likely to influence trial success from deep analysis of systems-based pharmacogenomics. VantAI's in silico platform specializes in modelling complex protein-protein interactions, powering the discovery of biologics and protein degraders in addition to small-molecule drugs. It has helped leading biopharma partners launch new development programs--or revitalize old ones--at a fraction of the time and cost of traditional methods. For more information, please visit http://www.vant.ai.
