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Hardware/Software x Data x ML
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Scientist, engineer, and general imaging enthusiast with a varied background from customer-facing roles to hardware/software engineering. Extensive experience with Optical Microscopy, Super-resolution Microscopy, Computer Vision, Image analysis, Object Detection, and Software Development.
University of California, San Francisco
Masters, Biophysics
January 1, 2005 – January 1, 2009
University of Illinois Urbana-Champaign
B.S., Engineering Physics, Chemistry
January 1, 2001 – January 1, 2005
Eikon Therapeutics
Staff Engineer
October 1, 2021 – Present
CZ Biohub
R&D Engineer
June 1, 2018 – October 1, 2021
San Francisco Bay Area
Insight Data Science
Artificial Intelligence Fellow
January 1, 2018 – April 1, 2018
San Francisco Bay Area
Singular Bio, Inc. (Acquired by Invitae in June 2019)
Imaging Scientist
September 1, 2015 – August 1, 2017
San Francisco
Carl Zeiss Microscopy
Super Resolution Specialist
May 1, 2011 – September 1, 2015
USA, Canada
University of California, San Francisco
Jr Specialist, Super-Resolution Microscopy
January 1, 2010 – May 1, 2011
University of California, San Francisco
Graduate Student
January 1, 2005 – January 1, 2009
University of Illinois at Urbana-Champaign
Undergraduate, College of Engineering, Physics
August 1, 2001 – May 1, 2005
Cultural Fit Analysis
The candidate's background is heavily rooted in academic research and scientific R&D, which aligns well with organizations that value deep technical expertise and innovation. The transition from pure research to engineering roles demonstrates a practical application mindset. However, the project diversity is limited to scientific imaging, which might require adaptation to broader ML applications. The breadth of skills is focused on specific scientific instrumentation and image analysis, which may require further development in general-purpose ML frameworks and deployment practices for a typical ML Engineer role.
Soft Skills & Operational Fit
The candidate's career progression from research to R&D and Staff Engineer roles suggests adaptability and a capacity for problem-solving in complex technical environments. Experience managing product sales growth also indicates communication and strategic thinking, though direct evidence of collaboration or stress handling from the provided data is insufficient.