Drug Discovery Data Entry Associate

Schrödinger’s mission is to revolutionize drug discovery through the use of breakthrough computational methods. We are currently looking for outstanding individuals to join our drug discovery group and contribute to our rapidly expanding portfolio of drug discovery collaborations.

Our drug discovery group of around 60 scientists includes designers, modelers, computational chemists, medicinal chemists, crystallographers, biochemists, and biologists. The group is supported by more than 100 software developers and engineers. Three of the programs we’ve worked on in the past 7 years have progressed into the clinic and an additional one is expected to enter clinical trials this year.  For recent news on one of these programs, go to this website.

If you are interested in a career combining science and technology on drug discovery projects, we are eager to hear from you.  

Job Requirements:

  • Participate in drug discovery group projects
  • Research, curate and prepare computational chemistry data sets, including:
    • Search scientific journals, patents, and databases for potential data sources
    • Transfer data from source to computer files or database systems, including the 2D rendering of chemical matter
    • Verify data by comparing it to source documents and update existing data
  • Prepare and maintain drug discovery group chemical database content
    • Querying, exporting, and uploading data and structures
    • Retrieve data from the database or electronic files as requested
  • Participate in improving software and processes via early access usage, bug reporting, and outlining improvement requests

Essential Qualifications and Experience

  • Bachelor’s degree in chemistry, biology, or biochemistry 
  • Successful completion of at least one year of organic chemistry coursework
  • Familiarity with two-dimensional chemical structure representations, especially depictions of stereochemistry
  • Approach research in an organized fashion with a strong attention to detail
  • Practical experience with tabular data in common spreadsheet formats (e.g. MS Excel, Google Sheets, comma-separated or tab-separated values)
  • Motivated learner:
    • willing to take on new challenges; 
    • able to learn rapidly; 
    • accepting of constructive criticism;
    • tactfully admit mistakes and errors; and
    • adapting quickly to changing situations, methods and procedures

Desirable Skills

  • Experience with analyzing scientific journal articles
  • Experience with any of the following:
    • Spreadsheets (MS Excel, Google Sheets, CSV)
    • Online sources of scientific information (especially NCBI PubMed, RCSB PDB, UniProtKB, EMBL-EBI ChEMBL, CAS SciFinder, Elsevier Reaxys)
    • Unix and/or Linux
    • Scripting (shell, Python, Perl)
    • Version control (Git);
    • Research experience in chemistry or biology


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