In this role, you have the opportunity to
Play an active role in the research team by contributing creative ideas, designing and developing NLP-based innovation solutions in healthcare, resulting in patents that protect potential business expansion and transfers that guide the future direction of our business roadmap.
You are responsible for
- Solve business-related problems (Cardiology, Radiology, and Oncology Business) using NLP or clinical informatics techniques and deep understanding of the end user/customer needs.
- Create value and impact by delivering meaningful insights by using advanced technologies for analyzing and interpreting large clinical corpus.
- Develop the NLP-based innovation prototypes, delivers and implement as products with engineers.
- Create hypotheses and validated insights/solutions using AI/DL/ML techniques in the hospital settings.
- Document your innovation outcomes in a formal way such as patents, technical notes, as well as peer-reviewed publications
- Collaborating with colleagues from other groups internal or external of Philips working in related fields and assisting your colleagues with your data-driven innovation insights, both in China and abroad
- Support or coach & develop less experienced NLP scientists.
You are a part of
The PD (Precision Diagnosis) / IGT (Image Guided Therapy) department of Philips Research China, focusing on innovations using data mining, machine learning, and artificial intelligence in professional healthcare settings. A highly effective and efficient but positive workplace atmosphere is valued, and a diverse team with backgrounds not only in clinical medicine and biomedical informatics but also in computer science will greet you. You will collaborate with market and business teams as well as hospital professionals to accelerate innovations.
To succeed in this role, you should have the following skills and experience
- PhD degree in Biomedical Informatics, Computer Science, or related fields (working experience is preferred)
- Track records of publications in international conferences/journals
- Hands-on experience in NLP (e.g. word tokenization, named entity recognition, dependency parsing, knowledge graph building) and machine learning on realistic data-driven applications
- Experienced in Healthcare IT system/architecture, data model, terminology, or healthcare standards
- Experienced in Python, Java, Go, C++ or any other programming language
- Experienced in SQL, NoSQL or Graph Database
- Experience in NLP toolkits (e.g. NLTK, spaCy, cTAKES) or deep learning framework (e.g. PyTorch, Tensorflow, MXNet, etc)
- Evidence of strong project management skills
- Collaborative and communicative mindset with stakeholders such as clinical, R&D, business and academic professionals
- Fluency in written/spoken English and Chinese for technical writing and strong presentation skills
- Knowledge and experience in clinical practice and clinical trials is a plus
In return, we offer you
A path towards your most rewarding career. Philips is growing its Artificial Intelligence. Succeeding in this challenging role will open many doors for your long term career, in other areas in Philips or otherwise. We also believe that we are at our best as a company when you are at yours as a person. Thus, we offer competitive health benefits, a flexible work schedule and access to local well-being focused activities.
Why should you join Philips?
Working at Philips is more than a job. It’s a calling to create a healthier society through meaningful work, focused on improving 3 billion lives a year by delivering innovative solutions across the health continuum. Our people experience a variety of unexpected moments when their lives and careers come together in meaningful ways. Learn more by watching this video.
To find out more about what it’s like working for Philips at a personal level, visit the Working at Philips page on our career website, where you can read stories from our employee blog. Once there, you can also learn about our recruitment process, or find answers to some of the frequently asked questions.