PerceptiMed is a group of creative and energetic people building a revolutionary state of the art medication-verification system that dramatically improves safety within pharmacies, long-term care facilities and hospitals..
Provide expertise in machine learning and computer vision to innovate in algorithm design and development for range of computer vision technologies; use C/C++, numerical methods, neural communication, convolution theory, and Fourier transforms; design and implement multithreading models; research, design, develop, and test different classification algorithms to classify 3,000-4,000 different types of medications with very high accuracy (99.99%); develop and test different Support Vector Machines (SVM) for classifying medications; research and develop hierarchical classification algorithms to classify 3,000-4,000 different types of medications; research and develop techniques to automatically fine tune SVM classifiers; automate SVM build process; research and develop techniques to generate new image features to improve accuracy of the existing SVM classifiers; and code review peers’ codes.
Bachelor’s degree or foreign equivalent in Computer Science, Computer Engineering, or Electronics Engineering plus relevant coursework, internships, or experience to include using C/C++, numerical methods, neural communication, convolution theory and Fourier transforms; designing and implementing multithreading models. Experience and skills may be gained through academic coursework and concurrently while pursuing academic studies.
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