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Physics Informed AI/ML Researcher
Autodesk
Design and make software for architecture, engineering, construction, and entertainment industries.
Research & develop physics-informed AI/ML algorithms for design and simulation tools.
Consult with product teams on the implementation of research into products
Participate in research collaborations with external research institutes and universities
Publish papers in peer-reviewed scientific journals/conferences
Research and implement physics-informed AI/ML algorithms, and demonstrate their applicability to areas of interest for Autodesk
Work closely with a multi-disciplinary team of research scientists and engineers to conceive, plan, develop, and implement scientific research projects
Mentor or lead researchers, engineers and interns (undergraduate, graduate or post-doctoral)
Document and communicate the intent and the results of projects in clear terms to both technical and non-technical team audiences both internally and externally
Design and build physics-informed AI/ML workflows and data pipelines, create and curate training data, develop and test models
Promote the use of research findings throughout Autodesk
What you bring
python
c++
hpc
pytorch
phd
communication
Knowledge of computational geometry, topology and geometric deep learning
Ability to articulate how physics-informed AI methods relate to more traditional numerical methods, surrogate models, reduced order models and simulation approaches in, for example, CFD or computational mechanics
Excellent written and oral communication skills
Familiarity with best practices in data creation, data and workflow management as related to training AI/ML models
Python and C++. Familiarity with HPC techniques
Strong publication history in relevant conferences and journals
Familiarity with collaborative development environments and version control systems
Ability to collaborate effectively with a diverse, multicultural, global team of scientists, engineers and architects
Ability to quickly learn new technologies and adapt to new situations
Extensive experience with methods that combine modern machine learning and AI/ML methods with computational physics algorithms
Experience creating and training machine learning models at scale (e.g. using PyTorch, TensorFlow, Flax, etc)
PHD’s in Physics or Applied Mathematics, Computer Science, Engineering and 3+ yrs of professional experience
Excellent knowledge of computational physics and numerical methods, e.g. for deriving and solving the large linear and non-linear systems that arise from discretizing differential equations
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