CINF Scholarship for Scientific Excellence

Purpose

The scholarship program of the Division of Chemical Information (CINF) of the American Chemical Society (ACS) is designed to reward graduate and postdoctoral students in chemical information and related sciences for scientific excellence and to foster their involvement in CINF.

Scope

Scholarships valued at $1,000 each will be awarded at the ACS National Meetings.

Eligibility & Application

Applicants must:

  • be enrolled at a certified college or university.
  • present a poster during the CINF Welcoming Reception and the Sci-Mix session at the National Meeting.
  • Abstracts for the poster must be submitted electronically through the Meeting Abstracts Programming System (MAPS) according to ACS rules approximately three months in advance of the meeting in question.
  • send in electronic form a 2,000-word long abstract describing the work to be presented:
    • submitted to: Stuart Chalkdue by mid-June for presentation at the Fall Conference of that year.
    • due by mid-January for presentation at the Spring Conference of the upcoming year.

Any questions related to applying for one of the scholarships should also be directed to Stuart Chalk

Selection

Winners will be chosen based on content, presentation, and relevance of the poster, and they will be announced at the meeting. The content shall reflect upon the student’s work and describe research in the field of cheminformatics and related sciences. At the Sci-Mix session, winning posters will be marked as "Winner of ACS Publications CINF Scholarship Award for Scientific Excellence”

Recent Sponsors and Recipients

ACS Nat'l Sponsor Recipient/Poster Title
#254, Fall, 2017 ACS Publications Phyo Phyo Kyaw Zin, Department of Chemistry, Bioinformatics Research Center, North Carolina State University, Raleigh, NC 27695, USA
“PKS Enumerator Software to Explore the Chemical Space of Macrolides”
#254, Fall, 2017 ACS Publications Mohammad Atif Faiz Afzal, Department of Chemical and Biological Engineering, University at Buffalo, The State University of New York, Buffalo, New York, USA
“Deep learning approach for the fast and accurate prediction of optical properties of organic molecules”
#254, Fall, 2017 ACS Publications Jeremy R. Ash, Department of Chemistry, Bioinformatics Research Center, North Carolina State University, Raleigh, NC 27695, USA
“Cheminformatics Approach to Exploring and Modeling Trait-Associated Metabolic Profiles”
#253, Spring, 2017 ACS Publications Andrew McEachran, National Center for Computational Toxicology, Environmental Protection Agency, Research Triangle Park, North Carolina, USA
“Mobilizing EPA’s Comptox Chemistry Dashboard data on mobile devices”
#253, Spring, 2017 ACS Publications Matthew Seddon, Information School, University of Sheffield, Regent Court, 211 Portobello, Sheffield S1 4DP, UK
“Global spectral and diffusion geometry descriptors of 3D molecular shape for virtual screening”
#253, Spring, 2017 ACS Publications Christopher T. Lee, Department of Chemistry and Biochemistry, University of California - San Diego, La Jolla CA 92093, USA
“Investigating transport properties with multiscale computable mesh models from heterogeneous structural datasets”
#252, Fall, 2016 ACS Publications Mojtaba Haghighatlari, Department of Chemical and Biological Engineering, University at Buffalo, USA
“ChemML: A Machine Learning and Informatics Program Suite for the Chemical and Materials Sciences”
#252, Fall, 2016 ACS Publications George Van Den Driessche, Department of Chemistry, Bioinformatics Research Center, North Carolina State University, USA
“Forecasting Adverse Drug Reactions Triggered by the Common HLA-B*57:01 Variant”
#252, Fall, 2016 ACS Publications Nathanael Kazmierczak, Department of Chemistry & Biochemistry, Calvin College, USA
“Modeling spectrophotometric titration data: tracking error from the measurement, through the model, and to the targeted output parameters”
#251, Spring, 2016 Springer & InfoChem Wilian Augusto Cortopassi, Chemistry Research Laboratory, University of Oxford, Oxford, UK
“Prediction and quantification of cation-π interactions in ligand-bromodomain binding: Using quantum chemistry to capture electronic effects”
#251, Spring, 2016 Springer & InfoChem Iva Lukac, School of Pharmacy and Biomolecular Sciences, Liverpool John Moores University, Liverpool, UK
“Quantifying the effect that chemical environment exerts upon changes in property in matched molecular pairs analysis”
#251, Spring, 2016 Springer & InfoChem Yu-Chen Lo, Chemistry and Biochemistry, University of California, Los Angeles, Los Angeles, California, USA
“CSNAP: A new chemoinformatics approach for target identification using chemical similarity networks”