Arcadia Science
Quantitative Biologist
Emeryville, California · Contract
Sponsorship not specified$150k-$200kDetected 49 days ago
PythonCode ReviewMachine LearningData AnalysisBioinformaticsMicroscopyResearchExperimental DesignCommunication
About the role
- We're closing the gap between biological data and biological understanding.
- Read more about our work through our publications.
- You'll work with imaging modalities (Raman spectroscopy, coherent Raman imaging, live-cell microscopy, quantitative phase imaging) and a range of other quantitative measurements across diverse organisms.
Responsibilities
- Strong foundation in statistically driven experimental design with hands-on experience applying these to biological datasets
- Track record of working directly with experimental scientists to design, analyze, and interpret studies
- Demonstrated expertise developing software for biological image analysis
- In this role, you will work shoulder-to-shoulder with experimental biologists, and bring your own firsthand experience at the bench to inform how data is collected, analyzed, and interpreted.
Requirements
- Ph.D. or equivalent experience in biology, bioengineering, computational biology, biophysics, cell biology, or a related field
- At least 3 years of full-time relevant scientific experience post-PhD or equivalent
- Proficiency in Python and/or R for data analysis, pipeline development, and code review
- Experience with instrument control, data acquisition software, or pipelines connecting hardware to analysis
Compensation
- We provide competitive compensation and practical benefits to keep you happy and healthy so that you can do your best work.
Benefits
- Experience with statistical or machine learning methods applied to phenotypic biological data, including spectral or image data
- We provide competitive compensation and practical benefits to keep you happy and healthy so that you can do your best work.
Equal opportunity
- Arcadia is an equal opportunity workplace
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This listing is sourced directly from Arcadia Science's careers page and normalized into a canonical job model.