Bioimage Informatics Scientist - Image Analysis & Machine Learning

The Chan Zuckerberg Biohub San Francisco (CZ Biohub SF) (https://www.czbiohub.org/sf/) is an independent nonprofit research institute that brings together three powerhouse universities - Stanford, UC Berkeley, and UC San Francisco - into a single collaborative technology and discovery engine. CZ Biohub SF itself supports some of the brightest, boldest engineers, data scientists, and biomedical researchers to investigate the fundamental mechanisms underlying disease and develop new technologies that will lead to actionable diagnostics and effective therapies. We are guided by our values of scholarly excellence; disruptive innovation; hands-on engineering/hacking/building; partnership and collaboration; open communication and respect; inclusiveness; and opportunity for all.

Our Vision

• We pursue large scientific challenges that cannot be pursued in conventional environments
• We enable individual investigators to pursue their riskiest and most innovative ideas
• The technologies developed at CZ Biohub San Francisco facilitate research by scientists and clinicians at our home institutions and beyond

Diversity of thought, ideas, and perspectives are at the heart of CZ Biohub Network and enable disruptive innovation and scholarly excellence. We are committed to cultivating an inclusive organization where all colleagues feel inspired and know their work makes an important contribution.

The Opportunity

Come join an interdisciplinary team of biologists, data scientists and engineers! This position is a collaboration between the groups of Loic Royer and Manu Leonetti at the Chan Zuckerberg Biohub (https://www.czbiohub.org/royer, https://www.czbiohub.org/leonetti). We strive to map how the human cell is built by combining CRISPR, fluorescence microscopy, proteomics, robotics, software engineering and data science. We build large datasets and use them to develop new algorithms and analyses.  Our tools and data include:

- OpenCell (https://opencell.czbiohub.org/), a large reference of protein localization and interactions that can be mined and re-used by the entire community for discovery.
- innovative self-supervised machine learning algorithms like cytoself to encode protein localization patterns (https://github.com/royerlab/cytoself) or aydin to denoise images (https://github.com/royerlab/aydin). Royer’s team also co-founded napari (https://napari.org/), an interactive and multi-dimensional image viewer for Python with >10,000 users worldwide.

Our science is fully open-source and published in journals like Science and Nature Methods (https://bit.ly/3T5Fbmf; https://go.nature.com/3rXOSae; https://go.nature.com/3EEf9C9)

Our previous work showed how deep learning can help extract very specific functional information from images of cell morphology and protein localization ((https://bit.ly/3T5Fbmf; https://go.nature.com/3rXOSae). We are seeking a Bioimage Informatics Scientist - Image Analysis & Machine Learning to spearhead our next efforts to extract quantitative biological insights from millions of fluorescence microscopy images. This is an exciting opportunity to work at the leading edge of machine learning and systems biology, supported by experts in a highly collaborative and well-funded scientific environment.

What You'll Do

• Design pipelines for image processing of biological microscopy data
• Conceive novel deep learning-based algorithms to obtain new insights from our unique image datasets
• Partner with biology experts to identify and quantify cellular responses in response to a variety of perturbations (e.g., CRISPR screens, drug treatments, or viral infection)
• Explain technical concepts to a multi-disciplinary team of biologists, bioengineers, and data scientists at the Biohub
• Author publications & mentor junior colleagues

What You'll Bring

Essential –

• PhD in Computational Biology, Bioinformatics, Biophysics, or a related discipline. This can be waived if the candidate demonstrates exceptional knowledge and experience.
• At least 3 years of expertise in image processing and scientific programming in Python (e.g. NumPy, SciPy, scikit-image, TensorFlow, PyTorch