Scientist (AI Modeling for Computational Sciences)

As a Scientist at Aganitha, you will play a crucial role in utilizing cutting-edge advancements in computational chemistry, materials science, soft matter physics, AI/ML, and high-performance computing in the Cloud. Your contributions will be instrumental in accelerating design and development across various applications within Biopharma, consumer brands, and industrial materials. Key Responsibilities: - Design and develop AI/ML models to solve complex problems related to molecular properties, material behaviors, and reaction outcomes. - Develop and apply in silico methods for designing and optimizing therapeutic candidates, including antibodies, RNA molecules, and viral vectors. - Curate, process, and analyze scientific datasets from multiple sources to ensure data quality for model training. - Implement featurization strategies to accurately represent chemical structures, physical properties, and biological interactions. - Train and evaluate cutting-edge Machine Learning and Deep Learning algorithms to build predictive models. - Validate models against client-provided data and established benchmarks to ensure accuracy and utility. - Translate technical and scientific findings into clear insights for both technical and non-technical stakeholders. - Collaborate effectively with computational chemists, data scientists, and wet lab scientists to define project requirements and ensure successful deployment. - Stay updated on advancements in AI/ML, computational chemistry, and other relevant scientific domains to apply new methodologies. Qualifications: - PhD, post-doctoral research experience, or equivalent advanced studies in scientific disciplines like Biochemistry, Computational Biology, Bioinformatics, Computational Chemistry, etc. - Proficiency in Python programming. - Understanding of the ML/DL project lifecycle. - Strong problem-solving skills and critical thinking abilities. - Excellent verbal and written communication skills. Note: The job description does not contain any additional details about the company. As a Scientist at Aganitha, you will play a crucial role in utilizing cutting-edge advancements in computational chemistry, materials science, soft matter physics, AI/ML, and high-performance computing in the Cloud. Your contributions will be instrumental in accelerating design and development across various applications within Biopharma, consumer brands, and industrial materials. Key Responsibilities: - Design and develop AI/ML models to solve complex problems related to molecular properties, material behaviors, and reaction outcomes. - Develop and apply in silico methods for designing and optimizing therapeutic candidates, including antibodies, RNA molecules, and viral vectors. - Curate, process, and analyze scientific datasets from multiple sources to ensure data quality for model training. - Implement featurization strategies to accurately represent chemical structures, physical properties, and biological interactions. - Train and evaluate cutting-edge Machine Learning and Deep Learning algorithms to build predictive models. - Validate models against client-provided data and established benchmarks to ensure accuracy and utility. - Translate technical and scientific findings into clear insights for both technical and non-technical stakeholders. - Collaborate effectively with computational chemists, data scientists, and wet lab scientists to define project requirements and ensure successful deployment. - Stay updated on advancements in AI/ML, computational chemistry, and other relevant scientific domains to apply new methodologies. Qualifications: - PhD, post-doctoral research experience, or equivalent advanced studies in scientific disciplines like Biochemistry, Computational Biology, Bioinformatics, Computational Chemistry, etc. - Proficiency in Python programming. - Understanding of the ML/DL project lifecycle. - Strong problem-solving skills and critical thinking abilities. - Excellent verbal and written communication skills. Note: The job description does not contain any additional details about the company.