Job Description

Scientific Computation and Machine Learning Internship

Company: Siemens Foundational Technology (FT)

Company Overview

Siemens Foundational Technology (FT) serves as the central R&D department of Siemens, playing a crucial role in shaping the future of Siemens’ Simulation and Digital Twin technology. FT acts as a strategic partner to support the executive units across Siemens, with a primary research focus on future technologies for industry, infrastructure, mobility, and healthcare. This internship opportunity is within the Design and Simulation of Systems research team in Princeton, NJ.

This is an on-site, full-time position in Princeton, NJ, requiring a commitment of at least 3 months, with the potential for a hybrid arrangement if appropriate.

Role Summary

We are seeking a motivated and talented student intern with a background in simulation, machine learning, and optimization methods. The intern will be responsible for building engineering analysis and optimization workflows, leveraging both traditional numerical methods and machine learning techniques. This internship offers a unique opportunity to contribute to innovative industrial applications, working under the mentorship of experienced research professionals in an international environment.

Key Responsibilities

• Explore and build upon the latest ML-based protein/molecule modeling frameworks available.
• Integrate these models into high-order workflows and pipelines, including optimization and uncertainty quantification assessments.
• Test and benchmark the developed models using third-party or publicly available data.
• Collaborate with domain and subject matter experts to design and develop novel solutions for challenging real-world industrial problems.
• Document learnings and project progress, and regularly present results to the research and consulting team. Publication of results is encouraged where possible.

Education and Experience

• Enrolled in a Computer Science, Electrical Engineering, Statistics, Applied Mathematics, or a similar Engineering PhD program, specifically utilizing AI/ML approaches for Protein Modeling.

Basic Qualifications

• Ability to quickly learn and utilize new technologies and frameworks.
• Experience with setting up, training, testing, and evaluating ML models.
• Graduate-level coursework in Statistics, Data Modeling, and AI.
• Basic understanding of the latest ML approaches and architectures.
• Hands-on experience with software development in Python.
• Flexibility and resourcefulness to thrive in a growing, dynamic, and interdisciplinary team of specialists.
• Ability to work independently and manage time effectively.
• Proficiency in English (verbal & written).
• Legally authorized to work in the United States without corporate sponsorship now or in the future.

Preferred Skills

• Hands-on experience with Scientific Machine Learning.
• Familiarity with Linux systems and computational clusters (CPU/GPU).
• Basic experience in version control systems and agile development.
• Real-world problem-solving skills and a hands-on, can-do mentality.
• Eagerness to present proposals and results to a large audience.

Location: Princeton, NJ (On-site with potential for hybrid arrangement)

Employment Type: Full-time internship, at least 3 months

Compensation: $32-$47 per hour

Note: The position requires the candidate to be in the United States of America and hold a valid work permit for the US.

About Siemens

Siemens is a global technology company focused on industry, infrastructure, transport, and healthcare. We create technology with purpose, adding real value for customers through resource-efficient factories, resilient supply chains, smarter buildings and grids, sustainable transportation, and advanced healthcare solutions.

Our Commitment to Diversity, Equity, and Inclusion

Siemens values unique identities and perspectives, committed to providing equitable opportunities and building a workplace that reflects the diversity of society. We encourage you to bring your authentic self to create a better tomorrow with us. Learn more about our commitment to DEI here.

Protecting the environment, conserving natural resources, fostering the health and performance of our people, and safeguarding their working conditions are integral to Siemens’ social and business commitment, deeply embedded in our Business Conduct Guidelines and corporate strategy.

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