Sr. AAV Machine Learning Scientist
Our team is made up of leading scientific experts who are passionate about improving patients’ lives and easing the burden of these life-changing disorders for patients. We are looking for teammates with the ambition, creativity, and energy to help us build a unique organization.
If you are looking to be a part of a company with an entrepreneurial culture, a bold vision, and a meaningful purpose, Kriya is the company for you.
We are seeking an experienced machine learning scientist to lead research efforts at the intersection of AAV engineering and data science within our growing Technologies group. The ideal candidate will have significant experience designing and building machine learning models for translational biology. They will enjoy working collaboratively with AAV biologists, bioengineers, and laboratory scientists on a range of exciting scientific problems at the intersection of AAV gene therapy and machine learning. This is a unique opportunity to gain broad experience in a startup environment and to make a meaningful impact on patient outcomes.
Tasks & Responsibilities
- Lead exploratory analyses of functional genomic and molecular datasets
- Conceive and execute on computationally-driven hypotheses to accelerate AAV molecular engineering efforts
- Design and build deep learning models for biological phenotypes based on protein or nucleic acid sequence input data
- Read and provide feedback on scientific papers on emerging technologies at the intersection of AAV gene therapy and machine learning
- Document, communicate, and present work to a broad audience both internally and externally in the form of meetings, presentations, and publications.
- MS or PhD (preferred) in computer science, statistics, computational biology, molecular biology, bioengineering, or equivalent
- 3 years R&D experience in industry
- Advanced knowledge of a modern data-focused programming language, e.g. Python, R
- Fluency with at least one deep learning framework for neural networks (e.g., PyTorch, TensorFlow, Keras, or equivalent)
- Experience building machine learning models relating biological phenotype (e.g., structure/function) to protein or nucleic acid sequence
- Strong foundation in the scientific method, hypothesis testing, and machine learning study design
- Knowledge of Linux systems, including basic shell scripting
- Knowledge of cloud computing platforms such as AWS or GCP
- Experience at other biotechnology companies strongly preferred
- Experience with AAV or other gene therapy modalities
- Experience working with next-generation sequencing (NGS) data
- Experience with structural biology and software such as AlphaFold, PyMOL
- Experience with version control systems such as GitHub or Microsoft DevOps