Noetik is an AI-native biotechnology company that applies self-supervised machine learning to large-scale human multimodal spatial omics datasets with the aim of developing precision cancer therapies. Backed by DCVC (Data Collective).
About the role
We’re looking for an AI scientist to lead the development, training, and evaluation of custom world models of patient cancer biology. The models will be built using NOETIK’s extensive pan-cancer multimodal spatial dataset – the largest of its kind – combined with other datasets and modalities, and will be used for drug development, clinical trial design, and deep biological insight.
What they're looking for
- Publications and presentations in leading journals and machine learning conferences (e.g. NeurIPS, ICLR, ICML, CVPR)
- A PhD in a quantitative field using modern machine learning methods, or equivalent research experience
- Experience writing model architecture code and datasets in PyTorch, training and optimizing models, and evaluating trained models
- Deep knowledge of modern machine learning architectures and self-supervised learning approaches (autoencoders, diffusion, flow-matching, autoregressive decoders)
- Familiarity with training and inference in large-scale distributed systems, including advanced parallelism approaches and supporting frameworks
- Practical use of modern AI tools to accelerate scientific work without sacrificing integrity and rigor
More about this role
NOETIK is a frontier therapeutics company harnessing AI to deeply understand human biology and redefine clinical outcomes in oncology. Leveraging the largest proprietary multimodal oncology dataset of its kind, uniquely integrating deep spatial profiling with routine clinical assays, NOETIK’s foundation AI models precisely match therapeutic targets to patient subpopulations and accurately predict clinical efficacy. This AI-first approach elevates therapeutic development from probabilistic guesswork to precision science.
We’re looking for an AI scientist to lead the development, training, and evaluation of custom world models of patient cancer biology. The models will be built using NOETIK’s extensive pan-cancer multimodal spatial dataset – the largest of its kind – combined with other datasets and modalities, and will be used for drug development, clinical trial design, and deep biological insight. There is no blueprint for how to build models that make the most of this data; we’re looking for somebody who is excited to explore, experiment, and forge this field with us by developing new architectures, loss functions, and evals. The AI team at Noetik operates as a fast-paced...
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