Siemens Digital Industries Software
Deep Learning Researcher - PhysicsAI

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We are Siemens
Siemens Digital Industries Software is a leading provider of solutions for the design, simulation, and manufacture of products across many different industries. Formula 1 cars, ships, space exploration vehicles, and many of the objects we see in our daily lives are being conceived and manufactured using our software.
About the Role
Are you a Deep Learning Researcher who possess expertise in both deep learning and physics-based simulation? The PhysicsAI Team at Siemens is leveraging AI to reinvent the product design cycle. With a focus on customer impact and a strong culture of collaboration and innovation, our team is harnessing emerging technologies like 3D genAI and geometric deep learning to enable faster product design. The team’s expertise ranges from traditional engineering design and simulation, deep learning, computational geometry, design space exploration, and user experience.
If you'd like to be responsible for designing and investigating new methods for DL-based surrogate modelling and generative AI, testing them on industrial problems, and implementing them into Simcenter PhysicsAI then we'd love to hear from you!
Key Responsibilities
You’ll make a difference by:
- Identifying and investigating emerging deep learning technologies and their application to mechanical, aerospace, and civil engineering.
- Taking the most promising approaches all of the way to productization by writing high quality production code.
- Assessing opportunities and gaps in the current genAI technology to inform future methods development.
- Capturing customer needs for complex engineering design problems by working with application engineers and specialists.
Reasons to use Rodeo
I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?
Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.
Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.
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Graduate Consultant — 2026 Scheme
Why you're a good match
StrongYour economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.
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Every day your agent scans the market matching roles against what actually matters to you, not just keywords on a CV.
Why you're a good match
You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.
Experience fit
Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.
Only hits
No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.
Requirements
Your success is grounded in:
- Master’s or PhD in Computer Science, Engineering, Artificial Intelligence, Mathematics, Physics, or a related technical field
- Strong proven theoretical knowledge of deep learning fundamentals
- Strong familiarity with architectures like transformers, diffusion models, normalizing flows, and Graph Neural Networks (GNNs)
- Proven theoretical knowledge of physics-based simulation like Finite Element Analysis (FEA), Computational Fluid Dynamics (CFD)
- Strong theoretical background in Partial Differential Equations (PDEs) and associated numerical methods
- Experience with mesh-based processing algorithms
- Hands-on experience with major deep learning frameworks like PyTorch or TensorFlow
- Experience working on large, complex code bases
- Strong problem-solving skills and ability to communicate technical findings clearly
Nice if you have:
- Familiarity with deep learning applications to engineering simulation (“Physics AI”), like neural operators, Transolver, etc.
- Familiarity with industrial FEA and CFD tools, like STARCCM+, OptiStruct, etc.
- Publications in top-tier conferences or journals such as NeurIPS, ICML, ICLR, CVPR, ACL, etc.
- Experience with distributed training, model scaling, and GPU/accelerator-based workflows
- Familiarity with MLOps, experiment tracking, and model deployment
- Experience with cloud platforms such as AWS, Azure, or GCP
- Open-source contributions or evidence of research impact
- Experience collaborating across research and engineering teams


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Join our Digital World
At Siemens Software, flexibility is how we work- hybrid by default, built on trust and autonomy. Together, 30,000 people across more than 200 countries build technology that shapes the real world. You'll grow through real projects, strong technical peers, and global mobility, backed by the scale and benefits of an industrial software leader. We're committed to equality and inclusion, and we hire based on merit, skills, and impact. Bring your curiosity and creativity and help us shape tomorrow!
Compensation & Benefits
The salary range for this position is 53,600 to 91,100 and this role is eligible to earn incentive compensation. The actual compensation offered is based on the successful candidate's job-related skills, experience, and relevant education/training. Siemens offers health and wellness benefits to employees; you can access the benefits available in your country via the link: https://jobs.sw.siemens.com/benefits/
Diversity & Inclusion
We value equal opportunities and welcome applications from all candidates. At Siemens, we believe people who've had real experiences dealing with being different will excel as leaders. Let's foster a culture of creativity and innovation. We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.
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