Post Doctoral Researcher - Multimodal Knowledge Extraction and Reasoning
Core
Develop advanced AI methods for multimodal knowledge extraction and reasoning to support critical business and engineering decisions in energy and chemicals.
Role type
Postdoctoral Researcher (Multimodal AI & Knowledge Systems)
Builds
Next-generation AI systems transforming complex, heterogeneous data into actionable insights.
Domain
Energy, Chemicals, Industrial AI
Deliverable
production ML models | research
Required skills
Multimodal machine learning, Knowledge representation, Reasoning systems, Deep learning architectures, Python programming, Machine learning frameworks, Heterogeneous data handling
Preferred skills
Multimodal foundation models, Knowledge graph construction, Retrieval-augmented generation, Probabilistic reasoning, Scalable data pipelines, Scientific data application
Technologies
PyTorch, TensorFlow, JAX, Large Language Models, Knowledge Graphs
Responsibilities
Develop multimodal data fusion and representation learning methods; Design models for knowledge extraction (entity/relation recognition); Build reasoning systems combining neural and symbolic approaches; Construct and utilize knowledge graphs; Evaluate models for accuracy, robustness, and explainability; Collaborate with domain experts to translate knowledge into workflows; Implement scalable ML pipelines; Publish research findings.
Seniority
Postdoctoral Researcher (1-3 years duration)