Research Scientist: Computational & Applied Mathematics

Job Description

Right now, we’re powering a whole country, finding ways to prevent malaria, making cities smarter, developing renewable energy, designing 3D robots, transporting people at 250 mph and helping NASA explore Mars. Our experience has shown that key technology components coming from areas like AI, analytics, IOT, Cyber-Security, additive manufacturing and materials science are extremely relevant for such innovations. 

 Our central research and development unit, Corporate Technology (CT) plays an important role in this as a strategic partner to Siemens’ operative units. It provides important services along the entire value chain - from research and development to production and quality assurance, as well as optimized business processes. 

The Predictive Analytics group within Business Analytics and Monitoring (BAM) Technology Field of Siemens Corporate Technology (CT) is seeking a Research Scientist for our Princeton, NJ location with focus on Computation and Applied Mathematical techniques for Industrial Artificial Intelligence.
As a Research Scientist, you will be part of a multidisciplinary team that is excited to tackle industrial challenges using techniques from Statistical Learning, Mathematical Optimization, Systems Science. 

What will be my responsibilities? 
Develop ideas and technologies at the intersection of End 2 End Learning and Systems Modelling.
Develop proof of concept and prototypes addressing Siemens industrial applications
Extend Siemens brand value by publishing in high impact conferences and journals and through patent development
Collaborate with peers and external academic partners to secure government grants in relevant domains.
Develop and maintain relationships with key universities and institutes to expand technology portfolio and jointly pursue public funding opportunities.

What skills are needed to qualify?
PhD from a reputed organization in Computational and Applied Mathematics, Statistics, Operations Research, Computer Science, Electrical Engineering, and Mechanical Engineering, 
Demonstrable research and innovation track record (peer-reviewed publications, research monographs etc.)
Proven knowledge of AI/ML toolsets (PyTorch, Tensorflow etc.)
Proven development skills in Python or Java/C++
Excellent interpersonal and communication skills
Ability to multitask and anticipate project needs
Ability to work with controlled technology in accordance with US export control law 

Additional Preferred skills/experience:
Using machine learning for infinite dimensional physical systems 
Knowledge of Optimization & Control Theory
Experience in simulation techniques

Successful candidate must be able to work with controlled technology in accordance with US Export Control Law. 

US Export Control laws and applicable regulations govern the distribution of strategically important technology, services and information to foreign nationals and foreign countries. Siemens may require candidates under consideration for employment opportunities to submit information regarding citizenship status to allow the organization to comply with specific US Export Control laws and regulations. Additional information on the US Export Control laws & regulations can be found on http://www.bis.doc.gov/index.php/policy-guidance/deemed-exports/deemed-exports-faqs?view=category&id=33#subcat34



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Job ID: 190728

Organization: Corporate Technology

Company: Siemens Corporation

Experience Level: Early Professional

Job Type: Full-time



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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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