Philips Data Scientist – Image Processing Recruitment, Apply Online

Philips has announced a job opportunity for Data Scientist – Image Processing. With this recruiting, you might make about approximately Rs. ₹1,33,333/- per month. Excellent opportunity for those people who are looking for private job opportunities More details are given below.

Looking for private Jobs? Then refer to this careerbywell page. The link is at the end of the article for application. The last date of application isn’t given so apply ASAP.

About Philips

Koninklijke Philips N.V. (lit. ’Royal Philips’), commonly shortened to Philips, is a Dutch multinational conglomerate corporation that was founded in Eindhoven in 1891. Since 1997, it has been mostly headquartered in Amsterdam, though the Benelux headquarters is still in Eindhoven. Philips was formerly one of the largest electronics companies in the world, but is currently focused on the area of health technology, having divested its other divisions.

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Philips Recruitment 2023 Overview

Philips Your role

• Support NPI development and address time-pressing complex LCM challenges with image processing / IQ using expertise.
• Mentor and guide less experienced engineers from the team. A higher degree of learning attitude to absorb newer knowledge on medical image pre-and/or post-processing
• Ability to take on complex problems with ambiguity in medical image processing and deliver PoC with TRL level ready for NPI program.
• Actively collaborate with clinical scientists, AD leaders, and universities to drive advanced development projects on medical image analytics from an R&D perspective.

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Philips Recruitment You’re the right fit if

Expertise (hands-on work) in some of the following tools, packages, technical areas and modeling techniques:

• Medical image pre-processing techniques such as gain/offset correction, defect correction, EMI/EMC correction, grid correction and calibration depending on detector physics. Knowledge of overall IQ (image quality) analysis of diagnostic X-ray images is a plus.
• Good to have exposure & knowledge of
• Convolution Neural Networks, other statistical modeling & classification approaches (regression, SVM, PCA
• Matlab, python, R, Java/C/C++
• Opensource medical image visualization and segmentation tools like ITK, VTK