$160,000 - $250,000
Onsite – New Haven, Connecticut
A cutting-edge biotech startup is seeking a Senior Deep Learning Scientist to join their team. This innovative company is pioneering a first-of-its-kind platform to conduct preclinical studies, aiming to revolutionize the understanding and treatment of neurological diseases.
As a Senior Deep Learning Scientist, you will play a pivotal role in designing and implementing AI models that integrate complex biological signals. You'll be at the forefront of pioneering work in areas such as generative graph representation learning, contributing to the development of novel AI architectures tailored to the intricacies of human brain biology.
Key Responsibilities:
- Design, develop, and deploy state-of-the-art deep learning models for analyzing multi-modal biological data.
- Develop deep learning architectures incorporating biological inductive biases, and explore generative graph representation learning to uncover novel patterns in brain data.
- Work closely with bioinformatics, experimental biology, and engineering teams to integrate multi-modal datasets into cohesive AI frameworks.
- Optimize deep learning pipelines for petabyte-scale datasets and ensure models are scalable on high-performance computing infrastructures.
- Publish research findings and present at scientific conferences to contribute to the broader AI and biomedical communities.
Requirements:
- PhD or Post-doc in Computer Science, Machine Learning, or a related STEM field with a strong demonstrated track record of applying deep learning to biological problems.
- The ability to translate conceptual research frameworks into deployable architectures.
- Comfort working across research and applied implementation.
- Proven experience with GNNs and an ability to tailor these methods to biological data. Experience with generative graph representation learning is a significant plus.
- Expertise in PyTorch with the ability to build and deploy scalable models.
- Familiarity with developing production-quality pipelines, cloud computing, and model deployment best practices.
- Demonstrated ability to research and implement novel deep learning architectures tailored to complex biological datasets.
- Experience with high-performance computing (HPC) environments or distributed training techniques for large-scale GNN models.
Apply now or reach out to Ben at benjamin@deeprec.ai to learn more!
