About the job
Charter:
Join us as a pioneering member of a team dedicated to developing groundbreaking AI technologies aimed at replacing traditional lab and animal toxicity experiments with advanced AI models.
About Axiom:
At Axiom, we are revolutionizing preclinical safety through the creation of AI models that predict human toxicity more effectively than conventional animal tests and outdated in vitro assays. We seek an innovative computational biologist who excels at the convergence of high-dimensional data analysis, cellular biology, and machine learning. Collaborating with a premier team of scientists and engineers, you will develop predictive models based on imaging and functional biochemical data, providing insights that influence real-world drug development. This role is ideal for those passionate about transforming biological signals into actionable insights, designing innovative assays, and partnering with leading pharmaceutical companies to accelerate safer and more human-centric drug discovery.
What We Seek:
We are eager to hire individuals who inspire us and challenge us to excel. You will elevate the entire team with your vibrant energy and profound sense of purpose. We look for candidates who possess a refined sense of priority, a keen eye for necessity, and an unwavering commitment to action. A deep-seated curiosity about all aspects of Axiom and an ambitious drive should fuel your enthusiasm for our mission. You must be a technically proficient and dedicated expert in your field, driven by the challenge of tackling complex scientific problems and contributing to a generational company.
Your Responsibilities:
Lead the exploration and analysis of extensive multimodal toxicity datasets.
Convert complex, high-dimensional biological data into clear, actionable insights by identifying key signals.
Discover novel biological signals that distinguish safe drugs from toxic ones.
Perform comprehensive error analyses on machine learning models to clarify the biological insights captured by algorithms.
Develop innovative algorithms that bridge computation and biology to model unexplored biological mechanisms.
Examine diverse biological systems including liver, heart, kidney, and immune tissues to enhance drug safety assessments.
