Neuroscience Data Analyst

at  Princeton University

Overview:
The Princeton Neuroscience Institute has a Data Analyst position available in the Brain Registration and Histology Core Facility of BRAIN CoGS (www.braincogs.org). This multi-laboratory project seeks to understand how multiple brain regions work together to carry out cognitive processing, using mice as a model system for mammalian brain function. BRAIN CoGS is a collaboration between the labs of Carlos Brody, Mark Goldman (UC Davis), Jonathan Pillow, Sebastian Seung, David Tank, Sam Wang, and Ilana Witten.
The individual in this role will support BRAIN CoGS laboratories as a data analyst. They will collaborate with graduate students, postdoctoral research fellows, and software developers in the participating laboratories regarding experimental design, acquisition of histological and anatomical data, and analysis. The principal activities are to acquire microscopy data sets from neural tissue, and then perform post-experiment alignment, reconstruction, and analysis of the images. This is a one-year position with the possibility of renewal based on funding and performance. A commitment of at least two years is preferred.

Responsibilities:

• Quantitative analysis of fluorescence signals, including automatic cell recognition using deep learning and custom Python scripts.
• Operating fluorescence microscopes (light-sheet, epi-fluorescence/slide scanner)
• Computer-based volumetric reconstruction of whole brain images
• Computer-based registration of whole brain images to standardized atlases
• Curation and archival of data to public facing resources for used by the greater scientific community

Qualifications:
The ideal applicant will be an energetic, self-directed person with previous experience in imaging data analysis (using Python or MATLAB, microscopy and animal tissue handling.

Essential Qualifications:

• A bachelor’s degree or higher in a science, engineering or computing-related field
• Python or MATLAB programming experience
• Experience with microscopy data - either through image acquisition or data analysis

Highly Preferred Qualifications:

• Wet lab and/or tissue handling experience
• Experience working in a research environment
• Familiarity with Python including mathematical packages (numpy, pandas, scipy), Linux/Unix, and GitHub

This position is subject to the University’s background check policy.
Princeton University is an Equal Opportunity/Affirmative Action Employer and all qualified applicants will receive consideration for employment without regard to age, race, color, religion, sex, sexual orientation, gender identity or expression, national origin, disability status, protected veteran status, or any other characteristic protected by law. KNOW YOUR RIGHTS
Standard Weekly Hours: 36.25 Eligible for Overtime: Yes Benefits Eligible: Yes Probationary Period: 90 days Essential Services Personnel (see policy for detail): No Physical Capacity Exam Required: No Valid Driver’s License Required: No : #LI-ZY

• Quantitative analysis of fluorescence signals, including automatic cell recognition using deep learning and custom Python scripts.
• Operating fluorescence microscopes (light-sheet, epi-fluorescence/slide scanner)
• Computer-based volumetric reconstruction of whole brain images
• Computer-based registration of whole brain images to standardized atlases
• Curation and archival of data to public facing resources for used by the greater scientific communit