Materials Informatics and Optoelectronics Scientist - Hyderabad

Schrödinger is a science and technology leader with over 30 years of experience developing software solutions for physics-based and machine learning-based chemical simulations and predictive analyses.

We’re seeking an application-focused Materials Informatics & Optoelectronics Scientist to join us in our mission to improve human health and quality of life through the development, distribution, and application of advanced computational methods. As a member of our Materials Science team, you’ll have the opportunity to work on diverse projects in optoelectronics, catalysis, energy storage, semiconductors, aerospace, and specialty chemicals.

Who will love this job:

• A statistical and machine learning expert with robust problem-solving skills
• A materials science enthusiast who’s familiar with RDkit, MatMiner, Dscribe, or other informatics packages
• A proficient Python programmer and debugger who’s familiar with machine learning packages like Scikit-Learn, Pandas, NumPy, SciPy, and PyTorch
• An experienced researcher with hands-on experience in extracting datasets using large language models (LLM) or Optical Character Recognition (OCR) technologies
• A specialist in quantum chemistry or materials science who enjoys collaborating with an interdisciplinary team in a fast-paced environment

What you’ll do:

• Research, curate, and analyze datasets from literature and other sources using advanced techniques such as LLMs and OCR.
• Work with domain experts to ensure the accuracy and quality of data (such as molecular structures, SMILES strings, experimental measurements, etc)
• Develop and validate predictive machine learning models for OLED devices and other optoelectronic applications
• Communicate results and present ideas to the team
• Develop tools and workflows that can be integrated into commercial software products
• Validate existing Schrödinger machine learning products using public datasets or internally generated datasets

What you should have:

• A PhD in Chemistry or Materials Science
• Hands-on experience with the application of machine learning, neural networks, deep learning, data analysis, or chemical informatics to materials and complex chemicals
• Experience with LLM, OCR technologies, and the extraction of datasets for ML model development