Materials Informatics and Optoelectronics Scientist - Hyderabad

As a science and technology leader with over 30 years of experience in developing software solutions for physics-based and machine learning-based chemical simulations and predictive analyses, Schrdinger is looking for an application-focused Materials Informatics & Optoelectronics Scientist to join in the mission of improving human health and quality of life through the application of advanced computational methods. Joining the Materials Science team at Schrdinger will provide you with the opportunity to work on diverse projects in optoelectronics, catalysis, energy storage, semiconductors, aerospace, and specialty chemicals. You will love this job if you are a statistical and machine learning expert with robust problem-solving skills, a materials science enthusiast familiar with RDkit, MatMiner, Dscribe, or other informatics packages, a proficient Python programmer and debugger with knowledge of 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, and a specialist in quantum chemistry or materials science who enjoys collaborating with an interdisciplinary team in a fast-paced environment. Your responsibilities will include researching, curating, and analyzing datasets from literature and other sources using advanced techniques such as LLMs and OCR, working with domain experts to ensure the accuracy and quality of data (such as molecular structures, SMILES strings, experimental measurements, etc), developing and validating predictive machine learning models for OLED devices and other optoelectronic applications, communicating results and presenting ideas to the team, developing tools and workflows that can be integrated into commercial software products, and validating existing Schrdinger machine learning products using public datasets or internally generated datasets. To be successful in this role, you should hold a PhD in Chemistry or Materials Science, have hands-on experience with the application of machine learning, neural networks, deep learning, data analysis, or chemical informatics to materials and complex chemicals, and experience with LLM, OCR technologies, and the extraction of datasets for ML model development.,