3T Biosciences will bring something that the field of immunotherapy sorely needs – targets that will help us bring therapies to cure cancer in broad populations. We are developing transformative T cell receptor therapies for cancer and other immune-related diseases. Our proprietary technology allows us to identify T cell receptor targets as well as potential off-targets to combat clinical toxicities.
We’re committed to making a difference for patients. Our creative, dynamic, and out-of-the box thinking makes 3T Biosciences the perfect engine to drive therapeutic solutions to reality. We’re looking for enthusiastic and bright-minded individuals to bring their talents to a cohesive and ambitious team.
Your Typical Responsibilities:
- Building, testing, optimizing, and executing statistical and/or machine learning models (support vector machines, random forests, convolutional neural networks, etc.) related to DNA/RNA/protein data for novel target discovery
- Working in a small team of 3-4 computationalists to develop interdisciplinary skills in data infrastructure, data pipelines, scaling and automating pipelines, and computational biology
- Interfacing with a team of computational and experimental biologists to aid in experimental and computational designs
- Collaboration with the Therapeutic Discovery and Protein Engineering teams
Master’s or PhD degree or equivalent in relevant field
Experience in building and testing statistical and/or machine learning models (support vector machines, random forests, convolutional neural networks, etc.)
Self-motivated and a proactive thinker – can work independently and in teams
Relevant experience in statistics and machine learning
Excellent written and communication skills presenting and discussing scientific data
- 2+ years of industry experience relevant to statistical modeling and/or machine learning
Previous roles in managing teams and projects
- Knowledge in any of the following fields: structural biology, immunology, protein engineering, cancer biology
- Experience in applying computational models to protein structure data (affinity prediction, protein-protein docking, homology-based predictions, physics-based predictions)
- Experience analyzing next-generation sequencing data (exome, RNA, genome)
- Experience utilizing Amazon Web Services tools to scale and automate pipelines
- Parallel computing strategies to accelerate data analysis
Please contact firstname.lastname@example.org with your cover letter and resume.