Nosis Bio is an AI biotech on a mission to end chronic disease. Recent breakthroughs in programmable RNA therapeutics such as siRNAs and ASOs have opened the door to more effective treatments of many diseases, but delivering these therapies to tissues other than the liver has remained an elusive “holy grail” challenge. Nosis has solved this problem via physics-aware deep learning that includes novel neural net architectures, diffusion-based generative algorithms for molecular designs, and high-throughput biochemical assays for confirmatory real-world testing. Together with a best-in-class team of biologists and chemists, we have proven our medicines can be delivered anywhere in the body and can halt, and even revert, the progression of disease. We are deploying this highly differentiated technology across our multiple partnerships with the largest pharma companies in the world, and we have a pipeline of drugs showing best-in-class results against several multiple diseases.
We are looking for a world-class machine learning scientist to join us on the mission to make these computationally designed therapeutics the standard-of-care for all chronic diseases.
About the role
Solving a problem as crucial and difficult as drug delivery involves designing large complex molecules with tens of thousands of atomic interactions leading to dozens of emergent properties that must be optimized simultaneously. In the same way convolutional nets enabled breakthroughs in computer vision and transformers enabled breakthroughs in NLP, the ML team at Nosis has invented novel physics-informed deep learning architectures designed specifically to solve drug delivery. We are looking for a mission-aligned machine learning scientist who is eager to apply their skills and knowledge to improve and build upon this technology, with the end goal of designing medicines that will increase the quality and quantity of patients’ lives.
At Nosis, we embrace big challenges with enthusiasm and a first principles mindset. If that sounds like you, then we should talk!
What you will be doing
- Expanding and improving our physics-aware deep learning platform.
- Enhancing generative algorithms for designing molecules.
- Adding new capabilities to our platform, such as predicting and designing molecules with new chemical and biological properties.
- Developing novel approaches for modeling protein kinetics and dynamics.
- Working with some of the best molecular biologists and biochemists in the world to test and iterate on the molecules designed by the platform, as well as generate new data to improve our algorithms.
What we are looking for
- PhD in computer science, math, physics, or statistics.
- Proven track record of inventing and implementing novel deep learning architectures.
- Fluency in at least one deep learning platform, such as Pytorch, Tensorflow, or JAX.
- One or more publications in ML journals or conferences such as NeurIPS, ICML, ICLR, or JMLR
- Command of core scientific computing concepts including linear algebra, numerical optimization, etc.
A plus, but not required
- Experience with physics-aware deep learning.
- Experience with generative algorithms such as GANs, diffusion, or language model decoders.
- Proven ability to invent and deploy novel deep learning models in an industry setting.
Benefits
Our benefits include excellent medical and dental coverage, a generous compensation package, and unlimited vacation policy.
About Nosis Bio
Nosis was founded by a team of Stanford-trained ML scientists, molecular biologists, and chemists, all devoted to building a mission-driven company focused on creating better outcomes for patients. We are a well funded, venture-backed startup.
