Bioinformatics Scientist - Mass Spectrometry & Computational Biology

Key Skills

Java Programming, Python Programming, C++, C Programming, SQL, Cloud computing, Scala Programming, Machine learning techniques, Data science techniques, MATLAB Programming, PyTorch, TensorFlow, R Programming

Job Description

The Chan Zuckerberg Biohub is a one-of-a-kind 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 itself supports some of the brightest, boldest engineers, data scientists, and biomedical researchers to make breakthroughs in medicine and develop new technologies, frequently in collaboration with our partner universities. 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 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 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

The Chan Zuckerberg Biohub is currently seeking an outstanding Data Scientist to join the Quantitative Cell Science arm of the Data Sciences team. The successful applicant will work in collaboration with the Mass Spectrometry (MS) platform at CZ Biohub to build the next generation of multi-ome cell atlases. As part of the Data Sciences platform at the Biohub, our team builds tools and datasets that advance our understanding of health and disease. We are passionate about extracting meaningful information from whole organism cell atlases and inventing ways of interpreting, visualizing and sharing the data we generate. We are actively involved in single cell whole organism cell atlas construction, of note Tabula Sapiens, where we are leveraging conventional single-cell transcriptomics, histology, spatial transcriptomics, mass spectrometry and machine learning to advance the understanding of human biology. In line with the CZ Biohub mission, we are committed to open science and freely sharing data and code with the community.

The new team member will be in charge of performing MS data analyses for proteomics, metabolomics, and/or lipidomics experiments acquired with data-dependent (DDA) and -independent (DIA) workflows. Our goals include improving upon existing raw MS data analysis algorithms and pipelines; organizing data; engineering data pipelines to leverage common data formats, e.g. h5ad files; and to develop and implement analysis methods of processed MS data for project-specific needs. These implementations will dovetail with ongoing computational research underway at the CZ Biohub such as clustering and unsupervised learning, time series analysis and pathway analysis. The ideal candidate will be passionate about data integration for multimodal analysis with other data formats e.g. genomics and imaging, and be excited to work at the interface between mass spectrometry bench scientists and data scientists. This is an exciting opportunity to be embedded in a highly collaborative environment that promotes learning and skill development. For this position we are looking for a team player with a balance of strong technical skills, creativity, and excellent communication skills.

You will 

• Perform mass spectrometry data analysis for proteomics, metabolomics, and/or lipidomics experiments
• Organize and engineer data pipelines for processing raw mass spectrometry experimental output
• Implement pre-existing and develop novel analysis methods for post-processed mass spectrometry data, using methods including (but not limited to) unrestricted modification search, analysis of four-dimensional mass spectrometry data collected with timsTOF instruments, spectrum library utilization, and feature matching between data independent analysis (DIA) experiments.
• Be the contact point between the data sciences and the mass spectrometry platforms
• Clear and constant communication between multiple teams

You have

Essential –

• PhD or 3-5 years equivalent work experience in a quantitative, computational discipline such as computational biology, bioinformatics, statistics, applied mathematics, computer science, physics, engineering, etc.
• Experience with mass spectrometry data, e.g. proteomics, lipidomics, metabolomics
• Experience and familiarity with scientific programming languages and data science workflows (e.g. Python, numpy, scikit-learn, pandas, matplotlib, Jupyter notebook, etc.)
• Experience with statistical inference and time series analysis
• Strong communication skills and collaborative spirit
• Detail oriented with the ability to understand a system of complex interactions and explain it to technical and non-technical collaborators
• Capable of deep troubleshooting to discover the root causes of problems
• Experience with Git, or other version control workflows
• Comfortable in UNIX systems and working at the command line 
• Commitment to writing well-commented code and clear documentation
• Positive attitude, willingness to ask questions and learn independently

Feel free to apply even if not all qualifications are met, we are interested in candidates with strong technical qualifications even if not all the boxes are checked!

Nice to have - 

• Understanding of cell biology and next-generation sequencing
• experience with genomics data analysis and/or imaging data
• experience working with data generated by timsTOF and Thermo orbitrap mass spectrometers
• some bench experience with mass spectrometry and/or wet lab biology
• Experience with machine learning techniques and data engineering
• Understanding of real-time, data-dependent instrument control and algorithms
• Willingness to help and mentor team members with different levels of expertise

Chan Zuckerberg Biohub requires all employees, contractors, and interns, regardless of work location or type of role, to provide proof of full COVID-19 vaccination, including a booster vaccine dose, if eligible, by their start date. Those who are unable to get vaccinated or obtain a booster dose because of a disability, or who choose not to be vaccinated due to a sincerely held religious belief, practice, or observance must have an approved exception prior to their start date.

What We Provide

• Resources to disrupt and innovate at the frontiers of our knowledge of biology and disease
• A collegial and collaborative environment consisting of diverse expertise
• Existing collaborations within CZ Biohub: Technology Platforms (Bioengineering, Computational Microscopy, Data Science, Genomic Sequencing, Mass Spectrometry/Proteomics), Infectious Disease, and Quantitative Cell Science
• Access to collaborators, resources and facilities at our three partner universities (Stanford, UC Berkeley, and UC San Francisco) and at partner organizations in the Bay Area and beyond
• Competitive compensation and benefits commensurate with the experience

Benefits

We offer a robust benefits program that enables the important work Biohubbers do everyday. Our benefits include healthcare coverage, life and disability insurance, commuter subsidies, family planning services with fertility care, childcare stipend, 401(k) match, flexible time off and a generous parental leave policy. In addition, we honor our commitment to career development and our value of scholarly excellence through regular onsite opportunities to learn from the world's leading scientists.