Absentia Labs, Boston
We are looking for an AI Research Scientist to help advance the modeling approaches at the core of Absentia's platform.
This is a research role for someone who wants to develop new machine learning methods for difficult scientific problems, not simply apply existing models to biological datasets.
You will formulate research questions, design and run experiments, develop novel model architectures and learning strategies, and investigate how models can integrate heterogeneous biological and chemical evidence to predict complex human outcomes.
Our research problems span molecular representation, graph learning, transformers, multimodal learning, representation learning, uncertainty, mechanistic reasoning, and biological generalization.
You will work closely with our CTO, AI/ML engineers, data engineers, and scientists to move promising ideas from research hypotheses into validated modeling capabilities.
The goal is straightforward but difficult: develop AI systems that can reason about how a drug interacts with human biology well enough to make useful predictions before those outcomes are observed experimentally or clinically.
You are a researcher who is comfortable working where the correct modeling approach is not yet known.
You care about understanding why a model works, where it fails, and whether it is actually learning something generalizable.
You are comfortable moving between mathematical ideas, experimental code, scientific literature, and large-scale empirical results. You can pursue a research direction independently, but you also enjoy working closely with engineers and domain scientists to turn research into systems that matter.
Most importantly, you want your research to have consequences beyond a benchmark.
You do not need to come from drug development or toxicology. We care more about exceptional research ability and the capacity to learn new scientific domains.
Rather than hiring against a single architecture, we're interested in researchers who can attack questions such as:
Please submit your resume and a brief note describing your experience training large-scale models. Links to GitHub repositories, papers, or technical write-ups are encouraged.
Absentia Labs is building mechanistic AI models to predict how drug compounds will behave in the human body before costly preclinical and clinical studies.
Our platform integrates molecular properties, exposure, biological context, experimental evidence, and machine learning to identify potential safety liabilities earlier and explain the biological mechanisms driving them. We initially focus on predictive toxicology and drug safety, with the broader goal of building foundational models that can reason across human biology, pharmacology, and translational outcomes.
We work at the intersection of frontier AI, computational biology, chemistry, toxicology, and drug development.
Absentia Labs is an equal opportunity employer. We believe diverse teams build better systems and stronger science, and we encourage applicants from all backgrounds to apply.
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Source: the Absentia Labs Ashby job board. We last checked this job 10 h ago. We first saw it 8 days ago. A job on a job board does not always mean that the team interviews people now. We found this job board in a public list. We did not yet compare it with the careers page of the company.
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