Associate Computational Biologist at Chan Zuckerberg Biohub

San Francisco, California, United States -

Full Time

Start Date

Immediate

Expiry Date

30 Dec, 25

Salary

110000.0

Posted On

01 Oct, 25

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Computational Biology, Microscopy, Image Analysis, Python, MATLAB, C++, Teamwork, Communication, Problem-Solving, Deep Learning, Image Segmentation, Zebrafish, Data Acquisition, Biological Research, Software Development, HPC

Industry

Description

The Team The Chan Zuckerberg Biohub Network (https://www.czbiohub.org/) is a group of nonprofit research institutes that bring together scientists, engineers, and physicians with the goal of pursuing grand scientific challenges on 10- to 15-year time horizons. The CZ Biohub Network focuses on understanding underlying mechanisms of disease and developing new technologies that will lead to actionable diagnostics and effective therapies. 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 the CZ Biohub Network 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 organization where all colleagues feel inspired and know their work makes an important contribution. The Opportunity The Biohub Network has an interdisciplinary group that combining tools in high resolution imaging and computational image analysis and systems immunology in zebrafish to develop the first quantitative systems wide atlas of the immune system. As part of this effort, we are searching for an enthusiastic Associate Computational Biologist to accelerate our imaging and pipeline tool building efforts. The endeavor is a highly collaborative effort between various research groups at CZ Biohub and requires excellent communication skills, teamwork and problem-solving skills. The ideal candidate will have both strong computational skills related to developing analysis pipelines for imaging data as well experimental experience related to microscopy. The application requires a cover letter that describes Your interest in this role, the contributions you are excited to make, and skills you want to strengthen on the job Your professional goals and how this role can help you achieve them Any hobby projects relevant to the work We seek to recruit individuals with foundational skills, the ability to learn quickly, and the ability to pursue ambitious projects through collaborations. Prior experience related to the projects mentioned above is nice to have, but not required This role will be based in San Francisco initially, with a planned transition to Redwood City in two years. What You'll Do Work with scientists and engineers from diverse backgrounds to develop and apply pipelines for very large (10s of TBs) zebrafish immune system imaging datasets. Acquire data by performing live-imaging experiments with zebrafish on state-of-the-art custom-built microscopes Use existing image reconstruction, analysis, and visualization pipelines to facilitate biological interpretation. Troubleshoot and improve upon existing analysis methods Maintain systematic records of experiments and outcomes Discuss work at weekly group meetings, internal seminars, and external seminars Participate in publishing the work through software repositories, data repositories, and peer-reviewed papers What You'll Bring Essential – Bachelor’s degree in physics, engineering, computer science, or life science Candidates with a Master’s degree are also welcome to apply, however the role is not suitable for candidates with a doctoral degree 2+ years of coding experience (e.g. Python, MATLAB, or C++) with the ability to write clean, maintainable, and well-documented code Prior research experience (internship experience is considered) Exposure to working with microscopes (preferably custom-built) Excellent verbal and written communication skills Team player who can also work independently Nice to have - Prior experience developing pipelines Experience imaging in model systems (zebrafish is a plus) Experience using slurm, working within HPC environments Deep learning and use of existing image segmentation tools such as cellpose, SAM etc. Any experience with cell migration/ morphological characterization from imaging Prior experience with image analysis tools and libraries (e.g. scikit-image, OpenCV, pytorch, torchvision, ImageJ) Prior experience with biological research Compensation The San Francisco, CA base pay range for a new hire in this role is Associate Computational Biologist = $80,000.00 - $110,000.00 and Sr. Associate Computational Biologist = $92,000.00 - $127,000.00. New hires are typically hired into the lower portion of the range, enabling employee growth in the range over time. Actual placement in range is based on job-related skills and experience, as evaluated throughout the interview process. Benefits for the Whole You We’re thankful to have an incredible team behind our work. To honor their commitment, we offer a wide range of benefits to support the people who make all we do possible. Provides a generous employer match on employee 401(k) contributions to support planning for the future. Paid time off to volunteer at an organization of your choice. Funding for select family-forming benefits. Relocation support for employees who need assistance moving If you’re interested in a role but your previous experience doesn’t perfectly align with each qualification in the job description, we still encourage you to apply as you may be the perfect fit for this or another role. #LI-Onsite

Responsibilities

The Associate Computational Biologist will work with scientists and engineers to develop and apply pipelines for large zebrafish immune system imaging datasets. Responsibilities include acquiring data through live-imaging experiments, troubleshooting analysis methods, and participating in publishing research findings.