Job ID: 2020-12147 Type: Full-Time # of Openings: 1 Category: Information Technology
Do you have a background in computational research and love to write code? Do you want to help enable and advance groundbreaking computational social science research? If so, Princeton University's Research Computing department is recruiting a Research Software Engineer to join the fast growing Research Software Engineering (RSE) Group.
In the RSE Group, we collectively provide computational research expertise to multiple divisions within the University. As a central team of software experts, we are focused on improving the quality, performance, and sustainability of Princeton’s computational research software. Our group is committed to building collaborative environments in which the best software engineering practices are valued, and to sharing and applying cross-disciplinary computational techniques in new and emerging areas.
In this position, you will be an integral member of multiple research teams focused on cutting-edge social science research and machine learning. You will join teams of researchers associated with the Data Driven Social Science Initiative (DDSSI) and the Center for the Study of Democratic Politics (CSDP) to develop efficient and scalable research code by providing computational expertise in software development, algorithm selection, and optimization.
If you have a strong background in scientific programming or high performance computing, academic research, and an interest in contributing to computational social science you have the right skill set to make an immediate impact on multiple high-profile research projects. You will be poised to grow and expand your programming and data analytics expertise into a dynamic new set of research problems.
This position will require you to work closely with colleagues in the Office of Information Technology (OIT) as well as with faculty, student/postdoctoral researchers, and technical staff to enable and accelerate their research computing efforts.
Quickly understand underlying science, math, statistics, data analysis, and algorithms of computational research questions at a level sufficient to converse on Social Science topics with Princeton’s world-class researchers. This may consist of independent research (reading publications etc) and/or studying existing code bases.
Working independently, quickly translate research priorities into flexible software solutions that will meet potentially vague and nebulous requirements due to the inherent unpredictability of academic research.
Regularly meet with, listen to, and ask questions of researchers to ensure that engineered solutions fit the research need.
Communicate complex software engineering concepts with large project teams consisting of domain experts each with a varying degree of software engineering knowledge.
Identify appropriate solutions for each project and architect a set of applicable best practices uniquely appropriate for that project (e.g version control, continuous integration and continuous delivery, software design, programming model, etc.).
To ensure long term maintainability and sustainability of solutions document projects in a descriptive and appropriately detailed manner that can be understood by both researchers and future Research Software Engineers.
Provide technical expertise and guidance for improving the performance and quality of new and existing code bases.
Lead the design and construction of increasingly complex research software systems in a way that ensures projects are usable, maintainable, and sustainable.
Parallelize, debug, port, and tune existing research code to meet criteria set by the research needs.
Develop software tools that allow researchers to interact in flexible ways with extremely large data sets.
Understand and address software engineering questions that arise in research planning.
Maintain knowledge of current and future software development tools and techniques, programming languages, and high-performance computing hardware.
Continually keep abreast of a rapidly changing landscape of software engineering best practices, software development techniques, and computational research solutions.
Strong programming skills, particularly in the languages used in social science high-performance computing applications (e.g. C/C++, Python, R).
Demonstrated successes contributing to a collaborative research team.
Ability to work independently.
Ability to learn new systems beyond area of core knowledge.
Ability to communicate effectively with a diverse user base having varied levels of technical proficiencies.
Experience working in an academic research environment.
Experience tuning and optimizing research software and algorithms.
Experience working with very large data sets.
Experience developing research software outside of core domain knowledge.
Background in quantitative social science helpful, but not required.
A Bachelor’s degree is required. A graduate degree or equivalent experience in a research setting is preferred.
Princeton University is an Equal Opportunity/Affirmative Action Employer and all qualified applicants will receive consideration for employment without regard to age, race, color, religion, sex, sexual orientation, gender identity or expression, national origin, disability status, protected veteran status, or any other characteristic protected by law. EEO IS THE LAW
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