Materials Informatics and Optoelectronics Scientist

As an Application-Focused Materials Informatics & Optoelectronics Scientist at Schrdinger, you will be part of the Materials Science team working on diverse projects in optoelectronics, catalysis, energy storage, semiconductors, aerospace, and specialty chemicals. Your role will involve: - Researching, curating, and analyzing datasets using advanced techniques like Large Language Models (LLMs) and Optical Character Recognition (OCR). - Collaborating with domain experts to ensure data accuracy and quality, particularly concerning molecular structures, SMILES strings, and experimental measurements. - Developing and validating predictive machine learning models for OLED devices and other optoelectronic applications. - Communicating results, presenting ideas to the team, developing tools, and workflows for integration into commercial software products, and validating existing machine learning products. Qualifications Required: - Hold a PhD in Chemistry or Materials Science. - Possess hands-on experience in applying machine learning, neural networks, deep learning, data analysis, or chemical informatics to materials and complex chemicals. - Familiarity with RDKit, MatMiner, Dscribe, or other informatics packages. - Proficiency in Python programming and debugging. - Knowledge of machine learning packages like Scikit-Learn, Pandas, NumPy, SciPy, and PyTorch. - Experience with Large Language Models (LLMs) or Optical Character Recognition (OCR) technologies. - Enjoy collaborating with an interdisciplinary team in a fast-paced environment as a specialist in quantum chemistry or materials science. As an Application-Focused Materials Informatics & Optoelectronics Scientist at Schrdinger, you will be part of the Materials Science team working on diverse projects in optoelectronics, catalysis, energy storage, semiconductors, aerospace, and specialty chemicals. Your role will involve: - Researching, curating, and analyzing datasets using advanced techniques like Large Language Models (LLMs) and Optical Character Recognition (OCR). - Collaborating with domain experts to ensure data accuracy and quality, particularly concerning molecular structures, SMILES strings, and experimental measurements. - Developing and validating predictive machine learning models for OLED devices and other optoelectronic applications. - Communicating results, presenting ideas to the team, developing tools, and workflows for integration into commercial software products, and validating existing machine learning products. Qualifications Required: - Hold a PhD in Chemistry or Materials Science. - Possess hands-on experience in applying machine learning, neural networks, deep learning, data analysis, or chemical informatics to materials and complex chemicals. - Familiarity with RDKit, MatMiner, Dscribe, or other informatics packages. - Proficiency in Python programming and debugging. - Knowledge of machine learning packages like Scikit-Learn, Pandas, NumPy, SciPy, and PyTorch. - Experience with Large Language Models (LLMs) or Optical Character Recognition (OCR) technologies. - Enjoy collaborating with an interdisciplinary team in a fast-paced environment as a specialist in quantum chemistry or materials science.