[Remote] Postdoctoral Researcher - Machine Learning for Materials & Alloys

Note:The job is a remote job and is open to candidates in USA. SandboxAQ is a high-growth company delivering AI solutions that address some of the world's greatest challenges. The role involves developing and applying machine learning methods in materials science to support design and manufacturing processes. Responsibilities• Develop and apply ML and optimization techniques to guide lightweighting strategies. • Use reasoning-based ML approaches to evaluate trade-offs among performance, manufacturability and other criteria.• Apply Bayesian optimization and related uncertainty-aware methods to balance performance, manufacturability, and other constraints. • Build reproducible workflows that integrate materials data, manufacturing methods, and simulation outputs. • Curate and analyze structured datasets on materials, processing routes, and mechanical properties to support ML pipelines. • Collaborate with engineers and computer scientists to connect ML outputs with structural and materials design tasks. • Write technical reports and present results to technical and non-technical stakeholders.Skills• U.S. citizenship is required due to USG contract requirements. • PhD in Materials Science, Metallurgy, Mechanical Engineering, Computational Materials Science, Applied Physics, or a related field. • Demonstrated experience applying ML or statistical methods to materials or engineering applications. • Proficiency in Python and ML frameworks (PyTorch, TensorFlow, Scikit-learn). • Familiarity with optimization and uncertainty quantification methods such as Bayesian optimization, Gaussian processes, ensemble learning, or related approaches.• Strong research track record, evidenced by publications in materials science, ML, or computational design. • Excellent problem-solving and communication skills. • Familiarity with knowledge graphs or graph-based ML for materials/manufacturing data. • Experience with LLMs for data integration, retrieval-augmented reasoning, or decision support. • Experience with graph-based, generative, or physics-informed ML for materials or engineering applications. • Background in lightweighting, alloy substitutions, or design for manufacturability.• Experience working with experimental or simulation-based datasets in materials (e.g., thermomechanical processing data, microstructure characterization, or finite element modeling). • Ability to work collaboratively in multidisciplinary teams. Benefits• Annual discretionary bonuses• EquityCompany Overview• SandboxAQ develops AI and quantum technology solutions that enhance biopharma, cybersecurity, and materials science. It was founded in 2016, and is headquartered in Palo Alto, California, USA, with a workforce of 51-200 employees.Its website is Apply tot his job