Data & AI Scientist

Your responsibilities

• Apply and advance the state-of-the art machine learning techniques and adapt them for application in Philips products, services, software and solutions;
• Participate in research projects that address machine learning challenges and transfer the results to Philips businesses;
• Explore, experiment, and pilot concepts and applications;
• Scout for new technologies by visiting conferences, universities, vendors and monitor the literature and Internet sources;
• Keep abreast of technical, application and market developments in the relevant technological and industrial areas, showing interest in the business aspects;
• Contribute actively to a creative and inspiring working environment.

We are looking for

• An PhD (or MSc with 2+ years of relevant experience) in computer science or another relevant area providing good foundation in computer science, mathematics, and data science (including machine learning, deep learning and statistics);
• Proven capabilities in the domain of data science and hands-on experience machine learning, deep learning, computer vision;
• Python programming experience, strong software engineering culture and ability to write high-quality code;
• Fluent English (C1), excellent communication and technical writing skills;
• Affinity to the research way of working;
• Curious, enthusiastic, fast learner who loves machine learning and constantly grows own expertise, able to quickly pick up new areas, work Agile way and shares knowledge with others;
• Ability to understand and obtain customers user needs and be able to transform those into practical solutions;
• Team worker in multidisciplinary and international settings, ability to build strong personal relationships at all levels and with stakeholders, both internal and external to Philips Research;
• Experience with medical / healthcare domain is a plus.

Our Offer

• Competitive salary;
• A variable bonus based on both Philips results and personal performance;
• 28 days of annual leave;
• Excellent medical insurance;
• Healthy work-life balance;
• Flexible working schedule and hybrid/office/remote way of work;
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