We invite applications for a postdoctoral Research Computer Technology Fellowship at the Trottier Space Institute at McGill (TSI).
TSI is an interdisciplinary research centre within McGill University consisting of 20 affiliated faculty members from the Departments of Physics, Earth and Planetary Sciences, Atmospheric and Oceanic Sciences, and Natural Resource Sciences at McGill (see http://msi.mcgill.ca), as well as over 100 graduate postdoctoral researchers, students, and undergraduate researchers. Research topics include (but are not limited to) astrophysics, cosmology, astrobiology, geophysics, life in extreme environments, and the search for extraterrestrial biosignatures.
We seek strong candidates for a Research Computer Technology Fellow. The successful applicant will advise and collaborate on computational projects, including high-performance computing, machine learning, and advanced computational methods. They will be a resource person for TSI staff and researchers, including students. Their academic qualifications will be similar to those of a post-doctoral scholar (a degree in the physical sciences, math, engineering, or a similar discipline; an advanced degree in the physical sciences is an asset), with significant expertise in computational methods. Ideally, their scientific expertise will complement existing expertise at the TSI. They will also be the TSI liaison to the new McGill Computational and Data Systems Initiative (see https://www.mcgill.ca/cdsi). Because of the resource-person aspect of this position, which will include a training component (workshops and short courses), strong communication and interpersonal skills are required.
The successful applicant will have the opportunity to conduct independent research of their choosing in the computational sphere, for approximately 25% of their time. Salary will be commensurate with experience.
● performing computational or data science research, in collaboration with or in support of other TSI researchers;
● providing advice and expertise on computational and data analysis methods to interested TSI research groups;
● raising the level of expertise on data science at TSI, e.g. via workshops, tutorials, courses, etc.;
● participating in research groups for specific projects;
● providing an in-house forum for discussing computing-related problems and exchanging ideas at the technical level;
● investigating and testing new tools, and overseeing their implementation at TSI;
● assisting TSI’s researchers in using HPC and other computing resources for data analysis;
● supporting training that involves computational methods and data analysis;
● serving as required as a liaison with various external organizations providing relevant scientific resources and services, particularly McGill’s new Computational and Data Systems Initiative.
A degree in Physics, Mathematics, Computer Science, or a closely related discipline (an advanced degree is not necessary but would be an asset) and experience which necessitated the in-depth use of computational or data science methods and resources.
● familiarity and comfort with scientific / scientist culture and operating procedures;
● experience conducting research in Physics or Astrophysics (preferred) or a closely related discipline; i.e. direct familiarity with research processes;
● expert level computational science, data science, and IT skills, particularly with respect to researcher end user applications and tools;
● experience working in a team environment in a support role.
The candidate should:
● have a positive, outgoing personality with a genuine interest in engaging researchers and assisting them to improve their use of computational and data science algorithms;
● be a dynamic, quick-learner who can deal easily with the rapidly changing demands and possibilities of computational and data science, IT technology, and researcher needs;
● be able to build strong relationships within the research community and become a trusted, expert advisor;
● have strong verbal and written skills. The candidate must be able to demonstrate and communicate improved ways of applying data science through a variety of media and presentation methods;
● have the ability to advocate for the effective use of technology within the research community both within TSI and externally;
● demonstrate a teamwork-oriented problem solving attitude.
Applications must be submitted through AcademicJobsObline: https://academicjobsonline.org/ajo/jobs/24346
Applicants should submit a cover letter and a curriculum vitae (including a list of publications if applicable) and should arrange for three letters of recommendation to be sent through AcademicJobsOnline.