TRIUMF
Canada's National Laboratory for Particle and Nuclear Physics
STUDENT JOB PROGRAM
Summer 2020 job posting
Job number TR20-2-7

Position Title:

Junior Data Scientist 

Name of Project:

Deep Learning for Event Reconstruction in Water Cherenkov Detectors 

Overview:

Neutrino oscillations are the only experimentally verified observation of a process not described by the Standard Model of particle physics. Since their discovery in 1998 we have learnt a lot about the parameters that govern these oscillations, but there are still many questions remaining. Perhaps the most exciting of these is to determine whether neutrino oscillations violate charge-parity (CP) symmetry, and so could potentially explain why we live in a matter-dominated universe.

The T2K experiment and Nobel prize-winning Super-Kamiokande experiment are powerful tools for exploring neutrino oscillations. The next generation Hyper-Kamiokande experiment, coming online in the middle of the next decade, has significant discovery potential for CP violation, as well as other phenomenon such as proton decay, supernovae and other multi-messenger astronomical events, and dark matter. The Canadian group is working on a number of interesting R&D efforts aimed towards maximizing the potential of Hyper-K.

A background and a source of major systematic uncertainty in the CP violation analysis is caused by events where a gamma ray is produced in a neutrino interaction instead of the usual charged lepton (electron). The goal of this project is to develop a full data analysis chain for the measurement of this so called Neutral Current gamma (NCgamma) background in the intermediate (distance) water Cherenkov detector (IWCD) of the Hyper-K experiment. Supervised learning techniques such as Convolutional Neural Networks and perhaps more advanced models such as Graph Neural Networks and PointNets will be applied and tuned. The output of these networks will be implemented in a NCgamma interaction rate (cross-section) analysis including evaluation of statistical and simplified systematic uncertainties. Time permitting, generative deep learning methods can be applied to limit the impact of systematic effects. Such methods will include Generative Adversarial Networks (GANs) and their variants such as CycleGANs. Approaches with alternative generative methods such as Variational Auto Encoders (VAEs), will also be considered. The successful completion of the project will have a substantial impact on key scientific goals of both the Super-K and Hyper-K experiment, such as the CP violation measurement and other areas of particle physics and astronomy.

Duties:

Major duties include:
- Development and tuning of deep learning models for analysis of water Cherenkov data.
- Development and deployment of statistical data analysis tools.

Skills learned during this work experience:

- Experience in many aspects of a complicated physics problem. This will range from low level understanding of photosensors to the description of the high level capabilities of a next-generation neutrino experiment.

- Machine learning concepts and experience with deep learning libraries such as pytorch
- Experience with generative deep learning methods
- Critical thinking and problem solving
- Presentation skills from reports in regular meetings at national and international levels


Qualifications:

We are looking for a motivated physics student to work on an exciting high-energy physics project. The core skills that we are looking for include:
- Strong competence in the use of computational methods for data analysis.
- Ability to quickly learn new software tools and software packages.
- Experience with using Linux OS.
- Python programming experience.
- Experience with numerical libraries numpy, matplotlib
- Understanding of machine learning and deep learning concepts.
- Experience with deep learning and machine learning frameworks e.g. pytorch, scikit-learn
- Senior undergraduate level knowledge of Quantum Mechanics and electromagnetism
- Ability to independently solve problems and investigate alternatives.
Beneficial skills would include:
- Understanding of the basics of a particle physics detector.
- Understanding of concepts in probability theory and statistics.
- C++ programming experience
- Experience with batch processing systems (slurm, torque)
- Experience with versioning tools (git)

Shiftwork required:

No

Period of work:

May-August 2020 with possible 4-month extension  
Salary is commensurate with academic progress and previous relevant work experience, and ranges from $ 2080 to $ 2800 per month plus 4% vacation pay.
TRIUMF pays round-trip airfare (this does not apply to Vancouver/Victoria students); for Vancouver Island students, TRIUMF will pay ferry costs.

TRIUMF is an equal opportunity employer committed to diversity in the workplace, and we welcome applications from all qualified undergraduate students as defined below:

  • Canadian undergraduate students or Canadian Permanent Resident undergraduate students enrolled in an accredited post secondary institution in Canada (or outside Canada) who are studying in a vocational or professional training program that leads to a degree, diploma or certificate.
  • Foreign full-time undergraduate students currently enrolled at a designated learning institution at the post-secondary level, and who are studying in an academic, vocational or professional training program that leads to a degree, diploma or certificate that is at least six months in duration, and who have a valid Canadian study permit which allows for employment off-campus, and who have applied for a Social Insurance Number
  • Foreign undergraduate students enrolled in a recognized undergraduate program of study abroad who have accepted, or are in the process of accepting, an "Invitation to Apply" for a work permit under the International Experience Canada (IEC) program http://www.cic.gc.ca/english/work/iec/apply.asp

Applications must be received at TRIUMF by 4:00pm Pacific time on 2020-01-26.

To apply for any of the job postings, you must submit one application for each and every job for which you wish to be considered. Please combine all documents into one PDF for each job. All applications can be attached to one email in PDF format. Please do not send electronic documents in formats other than PDF. Please save the PDF as lastname-job number (eg Smith-15.pdf)

    An application consists of a:
  • Covering letter
  • Resume
  • Transcript of all post secondary grades (unofficial copies are accepted)
  • in addition, an online application form must be filled out for each job
    Applications must also clearly indicate:
  • The number of academic terms completed (i.e. terms, semesters, or quarters)
  • The number of work terms completed (or the equivalent)
  • The TRIUMF Job Number must be clearly stated in the covering letter

Students within an university co-op program MUST apply for TRIUMF jobs through their university co-op education office.

Email to:

student@triumf.ca

Mail to:

TRIUMF Student Program
Job Number TR20-2-7
4004 Wesbrook Mall
Vancouver, B.C.
V6T 2A3

No phone calls please. TRIUMF wishes to thank all applicants for their interest, and regrets that only those being considered will be contacted.

TRIUMF is located on the campus of the University of British Columbia.
For more information, visit our web site
http://www.triumf.ca