Your role and responsibilities
- Design and implement machine learning algorithms to derive novel insights from multimodal datasets by leveraging advance machine learning framework like PyTorch and TensorFlow
- Contribute to the development of foundational models and workflows for materials discovery
- Publish high impact factor research, file patents for novel methodologies, and present findings at prestigious conferences
- Stay at the forefront of emerging technologies and contribute to the development of cutting-edge tools and platforms
Required education
Doctorate Degree
Required technical and professional expertise
- PhD in Computational Chemistry, Machine Learning, Computational Biology, Bioinformatics, Computer Science, or a related field
- Proficiency in Python, SQL, and technologies like TensorFlow, PyTorch, CUDA, and Ray
- Familiarity with high-performance computing environments, cloud platforms (AWS, Google Cloud), and DevOps tools (Docker, GitHub Actions)
- A solid publication record demonstrating the ability to conduct and communicate impactful research
Preferred technical and professional experience
- Proficiency in test0driven development and continuous integration/continuous deployment (CI/CO) practices to ensure robust and scalable workflows
- Experience in knowledge engineering, machine learning, and scientific software development
- Familiarity with multi-agent framework (LangChain, LangGraph) and advanced RAG workflows
- Proven success in collaborating across disciplines to deliver innovative solutions
- Deep knowledge of computational biology, biochemstry, and/or material sciences
