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:
1) 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
2) Working in a small team of 5-6 computationalists to develop interdisciplinary skills in data infrastructure, data pipelines, scaling and automating pipelines, and bioinformatics
3) Collaborating with multiple internal groups on cross-functional projects
4) Creating presentations and providing written and verbal updates on scientific findings
1) 3+ years of industry experience relevant to statistical modeling and/or machine learning
2) Experience in building and testing statistical and/or machine learning models (support vector machines, random forests, convolutional neural networks, etc.)
3) Building and/or modifying scalable machine learning architectures (CNN, LSTM, etc.)
4) Experience scaling large deep learning networks
5) Self-motivated and a proactive thinker – can work independently and in teams
6) Relevant experience in statistics and machine learning
7) Excellent written and communication skills presenting and discussing scientific data
1) Master’s or PhD degree or equivalent in relevant field
2) Previous roles in managing teams and projects
3) Knowledge in any of the following fields: structural biology, immunology, protein engineering, cancer biology
4) Experience in applying computational models to protein structure data (affinity prediction, protein-protein docking, homology-based predictions, physics-based predictions)
5) Experience utilizing Amazon Web Services tools to scale and automate pipelines 6) Parallel computing strategies to accelerate data analysis
Please contact firstname.lastname@example.org with your cover letter and resume.