dream about better ways to understand what causes observed phenomena? Is
catching incorrect conclusions derived out of correlated data exciting to you?
Are forward casual inference and reverse causal questions motivating your
answered YES! to these questions and more
alike, come and join our team NOW, we NEED you!
Corporate Technology is looking for a talented Software Engineer with
deep know-how and interest in Numerics,
who would like to join our Product Design, Modeling and Simulation
(PSM-US) Research Group of the “Simulation and Digital Twin” Technology
Field, in the Tri-state area.
need your help to build the world's most advanced modeling, simulation and optimization
technology stack for large scale AI-driven
engineering and manufacturing toolchains , in collaboration with our
partner startups, leading academic institutions and government agencies. We're currently bringing onboard talented
scientist like you to research and build the algorithms powering our AI engine
to support engineering workflows with common-sense
and causal inference!
Our team is composed of makers, innovators, engineers and
scientists with deep technical expertise, who are passionate about
disruptive technologies in the areas of Modeling, Simulation, Engineering,
Control, Machine Learning and Optimization. Our deliverables enable the
successful transformation of the technology trends in Digital Twin into the business of the future for a
multitude of customer products and services.
Experienced candidates in these areas as well as those with
advanced degrees who have research background in these topics with the skills
and interest in applying their research and introducing innovative technologies
into Siemens products are encouraged to apply!
want to teach machines to model, simulate and optimize parts, products and
systems better than ever before and become perfect companions for engineers in
need to accelerate by 1000x their workflows. Our mission is to free engineers
from the burden of repetitive and non-creative tasks and allow them to truly
explore the immensity of their design spaces, efficiently and with confidence
in the results.
team is located in the wonderful Princeton NJ, a university town packed with
outstanding international talent that provide a unique feel to this true
cultural gem in the state. The town has plenty of activities to offer, but for
those looking for more, at just about 1-h drive we have NYC or Philly! We have the best public
schools in the country and all of the above glued together by a very active and
The candidates will be responsible for:
- Lead the research activities focused on topics that
are at the intersection of machine learning and causal reasoning, with
technology startups, leading academic institutions and government
- Leverage causal
insights to enhance the generalizability, fairness, performance or other
properties of machine learning methods.
- design, prototype, implement, evaluate and improve the
state of the art causal inference, counterfactual prediction, and causal
discovery algorithms using machine learning methods.
- develop algorithms
for applications of causal reasoning in engineering, physics, internet and
- Advance the state-of-the-art in the field, including
generating patents and publications in top journals and conferences.
- Communicate complex ideas and testing results
effectively, both orally and in writing, and provide recommendations and
support to internal engineering teams through accurate and effective
- Seeking advocacy from Siemens business units on
potential use cases, while educating and transferring
technologies back to Siemens businesses for product implementations.
- Collaborating with others, both within and outside
Siemens, to develop successful research proposals for external
funding that align with Siemens strategic direction
- PhD in Statistics , Mathematics, Computer Science, Physics, or equivalent, with 2+ years of related experience, with a well-established research track record as demonstrated by publications and open source software. Strong background in Machine Learning.
- Min of 3 years of Graduate research and internship experience in Causal Reasoning and Machine Learning.
- Proven ability to develop new research ideas as demonstrated by a strong publication record and early developments to the level of a working system prototype.
- Strong theoretical and practical background in statistical modeling, statistical pattern recognition, machine learning, sparse methods, applied mathematics, optimization.
- Outstanding coding skills and ability to write high quality code in Python, R and C++, “code it right the first time”
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 https://www.bis.doc.gov/index.php/policy-guidance/deemed-exports/deemed-exports-faqs
- Good communication and organization skills, with a logical approach to problem solving, good time management and task prioritization skills, with motivation to learn and use new technologies, work under uncertainty at fast pace, and ability to multitask and make key contributions to several projects.