Honda Research Institute USA, Inc

​B.S. degree in computer science, electrical engineering, material science, chemistry, chemical engineering, physics, or related fields. Knowledge of electrochemical material and experience in experiments. Ph. D. candidate in computer science, electrical engineering, material science, chemistry, chemical engineering, physics, or related fields. Experience in electrochemical material simulation. Experience in electrochemical material experimental testing

machine learning

This project is about using machine learning to aid the catalyst material design. It involves data collection, database curation, material property simulation, prediction, validation, and optimization. Time spanMay - Nov 2024, six months Key Responsibilities​During the time of the internship, you are expected to<ul><li>Assist material data collection and database curation</li><li>Assist machine learning algorithm development for material property prediction</li><li>Assist machine learning algorithm development for material optimization</li><li>Assist validation of material properties</li></ul> Minimum Qualifications<ul><li>​B.S. degree in computer science, electrical engineering, material science, chemistry, chemical engineering, physics, or related fields</li><li>Development experience in data-driven optimization</li><li>Knowledge of electrochemical material and experience in experiments</li><li>Strong skills in Python and ML tools</li></ul> Bonus Qualifications​<ul><li>Ph.D. candidate in computer science, electrical engineering, material science, chemistry, chemical engineering, physics, or related fields</li><li>Research experience in Bayesian optimization</li><li>Research experience in graphical neural networks</li><li>Research experience in machine learning for material design</li><li>Experience in electrochemical material simulation</li><li>Experience in electrochemical material experimental testing</li><li>Knowledge in density functional theory</li></ul> Position Keywords​material science, catalyst, chemistry, data-driven optimization, Bayesian optimization, machine learning Application method (through HRI career webpage)https://usa.honda-ri.com/intern-positions/-/asset_publisher/XabA3xZYmY9b/content/machine-learning-for-catalyst-material-design?_com_liferay_asset_publisher_web_portlet_AssetPublisherPortlet_INSTANCE_XabA3xZYmY9b_assetEntryId=1099571&_com_liferay_asset_publisher_web_portlet_AssetPublisherPortlet_INSTANCE_XabA3xZYmY9b_redirect=https%3A%2F%2Fusa.honda-ri.com%2Fintern-positions%3Fp_p_id%3Dcom_liferay_asset_publisher_web_portlet_AssetPublisherPortlet_INSTANCE_XabA3xZYmY9b%26p_p_lifecycle%3D0%26p_p_state%3Dnormal%26p_p_mode%3Dview%26_com_liferay_asset_publisher_web_portlet_AssetPublisherPortlet_INSTANCE_XabA3xZYmY9b_assetEntryId%3D1099571%26_com_liferay_asset_publisher_web_portlet_AssetPublisherPortlet_INSTANCE_XabA3xZYmY9b_cur%3D0%26p_r_p_resetCur%3Dfalse

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