Research Internship, Industrial Artificial Intelligence (AI)

Research Internship,
Industrial Artificial Intelligence (AI)
We are
looking for graduate interns to join our Physics Informed Artificial
Intelligence (PAI) research group in Princeton, NJ or remotely!

PAI is
part of Siemens central in-house research department - a strategic R&D partner
for Siemens businesses. At PAI we work on understanding how prior knowledge
can be brought into AI methods to facilitate robust solutions to the industrial
challenges of our Siemens businesses, such as Predictive Maintenance, Planning
and Control, Sustainable Design and many more.


The
Challenge
This
intern will:


Conduct applied
research in industrial artificial intelligence, with a focus on one of the
following topic areas:

Physics-Informed
AI-based differential simulation surrogates for fluid and rigid body dynamics
modeling and control in industrial metaverse applications
Symplectic integration schemes with
applications in Machine Learning (ML)
Simulation techniques, such as closure model
ML-assisted fast simulation for analog and
mixed signal circuit simulations
Data-centric
AI/ weak supervision application to multivariate time series big data
Graph machine learning,
graph mining
Industrial
Knowledge Graphs and Semantic Modelling

Design,
develop and implement (research) prototypes and demonstrators under the
guidance of your supervisor
Contribute to
our teams R&D projects
Create
technical reports, presentations and/or scientific papers

The
Candidate

Qualified candidates will have/be:
Currently pursuing
your MS or PhD in Computer Science, Symbolic Systems, Mathematics, Physics, Engineering,
or a related discipline
Preferably graduating
within the next 12 months and are considering a career in industrial research
Demonstrated ability
to work with Python or another programming language and have experience with two
or more:

Deep Learning libraries
such as TensorFlow, PyTorch or Julia
Physics-Aware
AI frameworks such as Modulus
Nvidias Warp,
Omniverse
Graph
databases, Semantic Web Technologies such as RDFS/OWL and SPARQL
Graph
Analytics, Graph Machine Learning frameworks

Excellent
communication skills, eager to learn and be part of diverse team
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
(link removed)




About Us

Siemens
Technology employees are passionate about applied research. We create
technology with purpose that benefits society - more agile and productive
factories, more intelligent and efficient buildings and grids, more reliable
and sustainable transportation. Our work powers Siemens products and is
regularly featured in patents and publications. We operate in a global
ecosystem focused on innovation, partnering with our customers, businesses,
government agencies, and leading academic institutions on highly visible
projects where collaboration is key.
Our people continuously develop their talents, are curious, and are not
afraid to take risks in pursuit of technological innovation. A strong learning
culture empowers employees at Siemens Technology to own their growth and development.
We know that diversity fuels innovation and drives business success. We
are committed to creating an inclusive environment, where diversity of thought,
culture, and experience is seen as our greatest strength. This is what brings
our best ideas to life.
We take pride in bringing our best selves to work every day,
prioritizing individual health, work-life blend, and flexibility.
At Siemens Technology, the success of our employees drives our success.


What
else do I need to know?



For more information please refer to our website at (link removed)







#LI-JS






Organization:
Technology

Company:
Siemens Corporation

Experience Level:
Student (Not Yet Graduated)

Full / Part time:
Full-time



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