Variational AI · Canada
Skills: Python, SQL
VANCOUVER, BC (OR REMOTE IN CANADA) / FULL TIME
Variational AI(https://himalayas.app/companies/variational-ai) is radically accelerating the development of promising drug candidates by integrating chemistry and pharmacology expertise with the state-of-the-art in machine learning. Traditional approaches to small molecule drug discovery require over ten years and two billion dollars, and their reliance on trial-and-error calls out for better predictive and generative models. The current industry standard has progressed little beyond shallow ML techniques and simple graph neural networks, largely due to the difficulty of integrating world-class machine learning research with traditional chemistry and pharmacology approaches. Variational AI(https://himalayas.app/companies/variational-ai) is building a generative foundation model for molecular structure and properties from the ground up. Over the past five years, we have been advancing the state-of-the-art, and delivering projects to customers including Merck, Rakovina Therapeutics, and ImmVue Therapeutics.
We are searching for a chemical data scientist / cheminformatician to join us in our quest to radically accelerate the development of new drugs through machine learning excellence. You will help:
identify, curate, and prepare datasets, ranging from potency and ADMET to gene expression and cell painting; characterize errors and noise in datasets, and develop techniques to filter and clean them; analyze curated datasets and integrate chemical data into our machine learning algorithms by designing data loaders; develop ligand- and structure-based featurizations; and apply traditional cheminformatics techniques.
In this process, you will have the opportunity to build your skills by collaborating with our team of accomplished ML scientists, computational chemists, and medicinal chemists.
Here is the background we’re looking for:
B.S., M.S., or Ph.D. in data science, statistics, computer science, physics, or related discipline, w…
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