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Computational Scientist, Machine Learning and Computer Vision

San Diego, California, USA

Full time



About the Role

Scientist will be expected to lead development and application of computational methods for analysis of spatial omics data together with more traditional microscopy images, in the context of biological studies of different diseases, aging and other processes impacting tissue homeostasis. Particular emphasis will be placed on analysis of tissue architectures, deciphering cell communications, and control of proliferation within tissues. Successful candidate will collaborate with both internal and external experimental groups, lead or participate in planning experimental designs, author and contribute to biological and methodological manuscripts, contribute to seminars and other scientific initiations within Altos as well as wider scientific community.

Who You Are

Minimum Qualifications

  • Expert knowledge deep learning methods and computer vision

  • Experience in developing tools in python, including modern machine learning frameworks (TensorFlow, PyTorch, JAX)

  • PhD. in Computer Science or a related discipline

  • Experience working at the intersection of computation and biology

  • Track record publications in peer-reviewed journals or conferences

  • An interest in carrying out genomics research in collaborative settings

Preferred Qualifications

  • Experience in analysis of microscopy or spatial omics data

  • Expertise in a large subset of the following: deep learning, reinforcement learning, generative models, language models, computer vision, Bayesian inference, causal reasoning & inference, transfer & multi-task learning, graph neural networks, active learning, hybrid mechanistic/ML models

  • Expertise in computational infrastructure for deep learning including GPUs, TPUs, cloud based machine learning

  • Working knowledge of R

  • Experience in developing tools in python, including modern machine learning frameworks (TensorFlow, PyTorch, JAX)

  • Familiarity with multi-omic integration or spatial transcriptomics analysis

The target salary for this role is: $127,500 - $172,500.

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