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Data Scientist/Digital Pathology - Tucson, United States - Solu Technology Partners
Description
Our partner ranks among the worlds prominent corporations in the biotechnology industry.Working on their team means youll impact the lives of millions of patients and be a part of a culture of innovation, curiosity, and diversity.
Summary:
Please note:
This is NOT a Software Engineering position.
Seeking candidates with Biomedical Imaging and Data Science Algorithm
Works with a highly collaborative team of scientists, engineers and software developers to solve image and data analysis problems in the field of Digital Pathology.
Contributes to research activities for technology assessment, internal project collaborations, and commercial medical devices. Implements technology in the fields of image processing, machine learning, pattern recognition and data mining. Organizes and tracks own deliverables.Experience in the design and development of
analysis algorithms for biomedical image data.
Hands-on experience with algorithm development for
image or data analysis algorithms.
Extensive experience with commonly used Deep
Learning models and frameworks (e.g., Pytorch,
Fastai, TensorFlow).
Product development experience with a focus on
data analysis.
Experience working with Digital Pathology tools or
Software.
Experience working with Medical devices.
Knowledge, Skill or Ability Req
Excellent written and verbal communication skills.
Biomedical Image Analysis a must
Good understanding of scientific principles; good analytical and mathematical skills.
Working knowledge and theoretical understanding of image analysis, pattern recognition,
machine learning, computer vision, and data mining methods.
Understanding and following of software engineering practices for prototyping and
commercial product development languages.
Basic understanding of biomedical image data, preferably in digital pathology.
*Solu Technology Partners provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, sexual orientation, national origin, age, disability or genetics.
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