Data and AI Scientist
Philips / Eindhoven (NL)Apply on site
In this role, you have the opportunity to carry out industrial research in the Artificial Intelligence (AI) field, having a huge impact on improving people's lives. You will apply, adjust and advance the state-of-the-art artificial intelligence techniques and use them in Philips products, services, software and solutions.
- Perform independent & industrial research, provide consultancy, and participate in projects in the area of AI, specifically by integrating knowledge-based with data-driven Machine Learning approaches or applying advanced machine learning with different types of data such as real-time location data, electronic health records or other hospital operational data to improve operation of Smart Hospitals of the future.
- Craft technologies that ensure proper AI functionality for Philips products and services. In addition, you contribute to AI strategy within the Research program. You have a full understanding of the state-of-the-art and build original contributions. You address important challenges in applying advanced AI techniques and tooling for specific application within healthcare and consumer lifestyle.
- Keep abreast of technical, application and market developments in the relevant technological and industrial areas, showing interest in the business aspects;
- Shape the definition and the strategy of the departments' research program;
- Contribute actively to a creative and inspiring working environment.
- The results of your work are adopted by Philips businesses, and are translated into successful products/services.
- External exposure (for example by means of patenting and scientific publications) and external collaborations (for example with universities or in the context of European research projects) are highly encouraged.
You are part of Philips Research, AI, Data Science & Digital Twin department: www.research.Philips.com.Our mission is to lead Philips into the Digital era through world-class innovations based on AI, data science and (bio)physics-based modeling. The focus of the department is on applying and advancing AI, data science and digital twin technologies to create key differentiators for Philips products, solutions and services. The department builds on several interconnected competences including machine learning, statistics, probability models, pattern recognition, computer vision, signal processing and data engineering. We use the advances in the aforementioned scientific disciplines, as well as new digital platforms to create innovation for Philips businesses by extracting insights from various sources like health records, vital signs, environmental sensors, mobile devices, Web, and social networking sites. Next to that, security and privacy are addressed and taken into account already in the design phase of Philips digital propositions. The department plays a crucial role in AI, digital and data-intensive research projects using these competencies.
We are looking for
- An MSc or PhD in computer science or another relevant area providing a good foundation in computer science, mathematics, and data science (including machine learning, deep learning and statistics);
- Affinity to the research way of working;
- Proven capabilities in the domain of data science and hands-on experience with particular sub-fields such as machine learning, statistics, deep learning, NLP;
- Experience and domain knowledge of the application of machine learning and data analytics technologies in the field of Smart hospitals, or specific departments such as an emergency department.
- Good communication and interpersonal skills, with the ability to build strong personal relationships at all levels and with all stakeholders, both internal and external to Philips Research;
- Ability to understand and obtain customers user needs and be able to transform those into practical solutions;
- Team worker in multidisciplinary and international settings, able to adapt quickly;
- Curious, enthusiastic, fast learner able to quickly pick up new areas and work Agile way;