About the Company
Life Science People are currently supporting an incredibly exciting, Y-Combinator funded start-up Biotech, aiming to transform drug discovery through the integrating of high throughput experimental biology, chemistry and machine learning to discover RNA - targeting therapies for human disease.
We are currently in the process of building the founding team, looking for a number of technical and scientific positions. You will be joining at a pivotal moment ahead of rapid company growth later this year and into 2022. The opportunity to join a business founded by an industry recognised scientific leader, within a pioneering field of science, alongside the opportunity to progress your career is on offer. We are looking for those with a desire to join a fast paced, fluid environment that will both be demanding yet incredible rewarding.
For the Machine Learning Research position, you will be leading the scientific and technical development of the machine learning pipelines at the intersection of RNA biology and chemistry. You will be the face of the company, presenting your work to the research community and conferences as well as working closely with the biologists and influencing experimental designs, target selection and progression of biology programs.
What we are looking for:
- PhD/MSc or equivalent in a quantitative field (e.g., computer science, computational biology, bioinformatics, statistics, or equivalent).
- Experience with RNA structure datasets and methods
- Knowledge of modern tools for ML such as Tensorflow, Pytorch.
- Understanding of both emerging and foundational machine learning methods (supervised/unsupervised) such as: linear/nonlinear methods for regression, classification, and dimensionality reduction, deep learning (CNNs, RNNs, GCN, transformers). Experience with graph based representations is a plus.
- Experience building research prototypes and developing product-worthy tools from them.
- Track record of collaborative research in machine learning, biology, and related fields.
Nice to have:
- Experience in mining features from large data sets
- Experience with MLOps frameworks such as TensorFlow Extended, Kubeflow, MLFlow.
- Experience with end-to-end ownership and engineering practices for AI/ML pipelines.
- Experience with cloud platforms (AWS, GCP, Azure).
- Experience with containerization and deployment of machine Learning models.
Please submit your CV or get in touch with Max Eldridge at Life Science People to register your interest.
The position can be based in either Toronto or the UK (London area preferable).