Research Scientist - NLP and Multimodal Machine Learning for Healthcare

Job Description

Organization: Siemens Healthineers
Business Unit: Digital Services
Requisition Number: 244615
Primary Location: United States-New Jersey-Princeton
Assignment Category: Full-time regular
Experience Level: Mid level
Education Required Level: Master's Degree
Travel Required: 5%

Job Description:


Each day approximately 5 million patients across the globe benefit from Siemens Healthineers’ innovative technologies and services. As a result, we have access to massive volumes of clinical data to train artificial intelligence (AI) models using our high performance computing resources (facilitating hundreds of AI experiments daily with 16 petaflops of computational power and growing). The Machine Intelligence Research Group at Siemens Healthineers, Princeton NJ, focuses on developing and implementing AI algorithms and prototypes that harness insights from multimodal data (primarily non-imaging data) to drive state-of-the-art healthcare customer services and support clinical decision making towards better patient outcomes at lower cost. Our excitement is fueled by our commitment to create breakthroughs in healthcare - by empowering healthcare providers towards expanding precision medicine, transforming care delivery, and improving patient experience. 


Key Responsibilities

The successful candidate would accomplish a wide variety of machine intelligence-related tasks such as:

-        performing research/investigation pertaining to the development and evaluation of new (and existing) techniques, algorithms, and processes for machine learning-based analytics, automated question answering using parallel inputs (image and speech), and natural language processing/NLP (including speech-enabled) applications

-        investigating use cases for these applications e.g. in the domains of medical diagnosis and healthcare customer service

-        creating and testing production-level prototypes and/or experimental models related to the use cases for the applications mentioned above

-        generating technical reports, charts, graphs, and other relevant documents to support productization of the prototypes/models

-        advising senior research and business stakeholders on various aspects of his/her work

-        identifying and applying problem-solving skills in addressing scientific and business challenges of interest to the company


-       PhD or MS  in computer science or related discipline

-       demonstrates and applies a broad knowledge of machine learning and NLP through successful completion of moderately complex assignments

-       familiar with fundamental concepts, practices, and principles of software development, version control, and scalable infrastructure/platforms

-       demonstrates strong hands-on experience in programming (Java, Python, C#, C++)

-       provides track record of publications & presentations at top-tier conferences/competitions

-       able to work well as individual contributor and within a multidisciplinary team



Working Relationships

-        Primarily intra-organizational contacts and external contacts

-        Provide general guidance or train support and/or professional staff, including interns






Equal Employment Opportunity Statement
Siemens is an Equal Opportunity and Affirmative Action Employer encouraging diversity in the workplace. All qualified applicants will receive consideration for employment without regard to their race, color, creed, religion, national origin, citizenship status, ancestry, sex, age, physical or mental disability, marital status, family responsibilities, pregnancy, genetic information, sexual orientation, gender expression, gender identity, transgender, sex stereotyping, protected veteran or military status, and other categories protected by federal, state or local law.

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Applicants and employees are protected under Federal law from discrimination. To learn more, Click here.

Pay Transparency Non-Discrimination Provision
Siemens follows Executive Order 11246, including the Pay Transparency Nondiscrimination Provision. To learn more, Click here.

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