Paris-Sud - 21 Feb 2018

This is an announcement for a research software engineer position opening at Université Paris-Sud, working on web-based user interfaces and semantic interoperability layers for mathematical computational systems and databases.

Time line

Interviews in March 2018 for a recruitment as soon as possible.

Update (March 27th): after the interviews on March 21st, we selected and ranked two candidates and made an offer to the first one. Pending administrative hoops, they will take the position.

Salary

For a full-time position, and depending on the applicant’s past experience, between 2000€ and 3000€ of monthly “salaire net” (salary after non-wage labour cost but before income tax). Equivalently, what this salary represents for is a “salaire brut” of up to 46200€ yearly. We have secured funding until the end of the project (August 2019).

Location

The research software engineer will work at the Laboratoire de Recherche en Informatique of Université Paris Sud, in the Orsay-Bures-Gif-Saclay campus, 25 km South-West of Paris city centre.

Mission and activities

Paris Sud is the leading site of OpenDreamKit, with eight participants involved in all the work packages. The research software engineer will join that team and support its efforts in WP4 and WP6, targeting respectively Jupyter-based user interfaces and interoperability for mathematical computational systems and databases. A common theme is how to best exploit the mathematical knowledge embedded in the systems. For some context, see e.g. the recent publications describing the Math-In-The-Middle approach.

More specifically, a successful candidate will be expected to contribute significantly to some of the following tasks (see also OpenDreamKit’s Proposal:

• Dynamic documentation and exploration system (Task 4.5)

  Introspection has become a critical tool in interactive computation, allowing user to explore, on the fly, the properties and capabilities of the objects under manipulation. This challenge becomes particularly acute in systems like Sage where large parts of the class hierarchy is built dynamically, and static documentation builders like Sphinx cannot anymore render all the available information.

  In this task, we will investigate how to further enhance the user experience. This will include:

  • On the fly generation of Javadoc style documentation, through introspection, allowing e.g. the exploration of the class hierarchy, available methods, etc.

  • Widgets based on the HTML5 and web component standards to display graphical views of the results of SPARQL queries, as well as populating data structures with the results of such queries,

  • D4.16: Exploratory support for semantic-aware interactive Jupyter widgets providing views on objects of the underlying computational or database components. Preliminary steps are demonstrated in the Larch Environment project (see demo videos) and sage-explorer. The ultimate aim would be to automatically generate LMFDB-style interfaces.

  Whenever possible, those features will be implemented generically for any computation kernel by extending the Jupyter protocol with introspection and documentation queries.

• Memoisation and production of new data (Task 6.9)

  Many CAS users run large and intensive computations, for which they want to collect the results while simultaneously working on software improvements. GAP retains computed attribute values of objects within a session; Sage currently has a limited cached_method. Neither offers storage that is persistent across sessions or supports publication of the result or sharing within a collaboration. We will use, extend and contribute back to, an appropriate established persistent memoisation infrastructure, such as python-joblib, redis-simple-cache or dogpile.cache, adding features needed for storage and use of results in mathematical research. We will design something that is simple to deploy and configure, and makes it easy to share results in a controlled manner, but provides enough assurance to enable the user to rely on the data, give proper credit to the original computation and rerun the computation if they want to.

• Knowledge-based code infrastructure (Task 6.5)

  Over the last decades, computational components, and in particular Axiom, MuPAD, GAP, or Sage, have embedded more and more mathematical knowledge directly inside the code, as a way to better structure it for expressiveness, flexibility, composability, documentation, and robustness. In this task we will review the various approaches taken in these software (e.g. categories and dynamic class hierarchies) and in proof assistants like Coq (e.g. static type systems), and compare their respective strength and weaknesses on concrete case studies. We will also explore whether paradigms offered by recent programming languages like Julia or Scala could enable a better implementation. Based on this we will suggest and experiment with design improvements, and explore challenges such as the compilation, verification, or interoperability of such code.

Skills and background requirements

• Degree in mathematics or computer science; PhD appreciated but not required;

• Strong programming experience with languages such as Python, Scala, Javascript, etc; experience with web technologies in general and the Jupyter stack in particular appreciated;

• Experience in software design and practical implementation in large software projects; experience with computational mathematics software (e.g. SageMath) appreciated;

• Experience in open-source development (collaborative development tools, interaction with the community, …);

• Strong communication skills;

• Fluency in oral and written English; speaking French is not a prerequisite.

Context

The position will be funded by OpenDreamKit, a Horizon 2020 European Research Infrastructure project that will run for four years, starting from September

1. This project brings together the open-source computational mathematics ecosystem – and in particular LinBox, MPIR, SageMath, GAP, PARI/GP, LMFDB, Singular, MathHub, and the IPython/Jupyter interactive computing environment. – toward building a flexible toolkit for Virtual Research Environments for mathematics. Lead by Université Paris-Sud, this project involves about 50 people spread over 15 sites in Europe, with a total budget of about 7.6 million euros.

Within this ecosystem, the applicant will work primarily on the free open-source mathematics software system Sagemath. Based on the Python language and many existing open-source math libraries, SageMath is developed since 10 years by a worldwide community of 300 researchers, teachers and engineers, and has reached 1.5M lines of code.

The applicant will work within one of the largest teams of SageMath developers, composed essentially of researchers in mathematics and computer science, at the Laboratoire de Recherche en Informatique (LRI) and in nearby institutions. The LRI also hosts a strong team working on proof systems.

Applications

To apply for this position, please send an e-mail to upsud-recruitement-research-engineer at opendreamkit.org by March 10, with the following documents (in English) attached:

• cover_letter.pdf: a cover letter explaining your interest in this particular position;

• CV.pdf: a CV, highlighting among other things your skills and background and your contributions to open source software;

• degree.pdf: copy of your most recent degree including (if applicable) the reviewers reports;

• reference letters: files reference_letter_.pdf or contact information of potential referees.

Applications sent after March 10 will be considered until the position is filled.

SageMath Jupyter WP6: Data/Knowledge/Software bases Math-in-the-Middle Job opening