Internship Opportunities: Designing Intelligent Experiences for Readable Spreadsheet Formulas

Last updated 25 days ago
Job Type:Full Time

The soul of the spreadsheet is the grid and its formulas.  Spreadsheets are the world’s most widely-used programming technology – but they also embody apparently-fundamental limitations. We are working on foundational ideas that will take a qualitative step forward, to extend dramatically the reach of what end users can do with spreadsheets.

A recent study conducted by the Calc Intelligence team at MSRC [1] identified the search for cell labels as being a top barrier to formula comprehension in spreadsheets. Design explorations show the potential for greatly increased intelligibility of formulas when cell references (such as A1), which do not contain any information about the value of the cell, are decorated with human-authored text ‘labels’ from nearby cells (e.g., ‘Q1 Sales’). In order to enable such experiences, we need to be able to reliably detect the presence of such labels, and which cells/ranges they refer to. This is the label inference problem. We are looking for an intern to work with our ML and HCI researchers to create and test working prototypes that build on top of the designs and ML model for label inference.

This is a design/HCI internship. You will not be expected to build the label inference model yourself, but rather work with other researchers who are building models to develop and test new user experiences. Results from your formative studies will feed into the fundamental design and approach of the models, and you may need to build simple heuristic models to bootstrap your own design explorations, and to provide a baseline for comparison.


Please ensure your application is submitted no later than Friday, February 5th 2021 (end of day, anywhere on earth).


[1] Sruti S Ragavan, Advait Sarkar, and Andrew D. Gordon. “Spreadsheet Comprehension: Guesswork, Giving up and Going back to the Author”. To appear in CHI 2021 (preprint available on request).


  • Work in a multi-disciplinary team
  • Explore new user experiences, visualizations to take advantage of label inference (this could be through design and/or engineering)
  • Conduct mixed methods user research (e.g., surveys, controlled experiments, ethnography, interviews etc.)
  • Translate findings into practical design insights
  • Analyse, write and present your findings in technical documents or papers
  • Develop and iterate on prototypes in collaboration with our engineering team, building on our existing platforms. This will involve building UI prototypes using React+TypeScript, or HTML+CSS+JS using other web front-end frameworks.
  • Deploy prototype technologies and evaluate their impact on user practice


  • Undertaking a PhD in human-computer interaction, end-user programming, human-factors in programming languages, or a related field. Outstanding undergraduate/Master’s students with research experience will also be considered.
  • Experience or interest in working in the spreadsheet domain
  • Experience of software prototyping at various levels of fidelity, from sketches and wireframes to interactive prototypes
  • One or two papers at top HCI, EUP, PL conferences, or journal articles are strongly desired. A writing sample of unpublished work should be included if a publication is not available.
  • Good spoken and written English

Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, color, family or medical care leave, gender identity or expression, genetic information, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran status, race, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable laws, regulations and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or the recruiting process, please send a request via the Accommodation request form.

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