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Jake Vikoren — 2026

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Physics-trained ML engineer · AI for Scientific Discovery

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Expertise

Focus Areas

🧬

AI for Biology

Applying deep learning to biomedical image analysis, protein structure prediction, and multi-modal model development to accelerate research at the cellular level.

Generative Modeling

Working with VAEs, Diffusion Models, and Flow Matching to design generative models for scientific applications.

👁️

Computer Vision

Transformer-based self-supervised learning for complex and nuanced understanding of visual data across domains.

📐

Geometric Deep Learning

Developing invariant and equivariant neural architectures leveraging the inherent symmetries of geometric data.

⚛️

Atomic-Scale Modeling

Leveraging my experience in physics and materials science to develop models and systems for atomic-scale simulations.

⚙️

Scalable ML Systems

Building and deploying production ML pipelines for large-scale scientific datasets in interdisciplinary research environments.


Get in Touch

Contact

I'm open to research collaborations, engineering roles, and conversations at the intersection of machine learning and science. Reach out on LinkedIn or explore my work on GitHub.