Requirements for these certificates are based on credit-hours of SciNet courses successfully completed. For a “short course” (typically a day long or shorter, with no between-course homework), a lecture hour counts as one credit hour; for a “long course” with homework due between sessions, a lecture hour counts as 1.5 credit hours. Courses offered by SciNet from January 2013 onwards will count towards these certificates. Students who have successfully taken SciNet courses before January 2013 may contact SciNet to discuss having credits applied from previously-taken courses.

Prerequisites

Some requirements such as programming skills vary per course; these are announced when the courses are announced, on SciNet’s course website: https://support.scinet.utoronto.ca/courses.

Many courses have a hands-on component that requires participants to bring their laptop.

Who can participate in the certificate program?

SciNet courses and certificates are open to all SciNet users (for some courses, a SciNet account is not necessary, but these are exceptions). In general, any academic researcher from a Canadian research institution with significant high performance computing requirements to support his or her research may apply for an account on SciNet. For information on how to get an account, go to http://www.scinethpc.ca/2011/09/getting-a-scinet-account.

Do the certificates count as University credentials?
No, the SciNet Certificates are not University credentials, and will not appear on transcripts. However, several SciNet courses are sometimes offered in cooperation with the Astronomy and Physics departments as graduate minicourses, which can count towards course credit; interested students in other departments are encouraged to contact SciNet and their graduate coordinator.

Can I attend the courses online?
Although we are looking into this, currently, this is not possible. You can only get credit for a course by physically attending it. Recordings and slides of many of the courses are, however, posted on the SciNet wiki afterwards: http://wiki.scinethpc.ca/wiki/index.php/Knowledge_Base:_Tutorials_and_Manuals

Certificate in Scientific Computing

Scientific computing is now an integral part of the scientific endevour. It is an interdisciplinary field that combines computer science, software development, physical sciences and numerical mathematics.

This certificate indicates that the holder has successfully completed at least 36 credit-hours worth of coursework in general scientific computing topics such as software development, version control, testing, visualization, and data management.

Requirements

• A total of 36 credit-hours or more from the list of SciNet courses on scientific computing given below.
• It is also possible to include credit-hours from the list of SciNet courses on high performance computing, but these credit-hours can then no longer be counted toward a Certificate in High Performance Computing.
• Upon completion of your certificate requirements, you must request your certificate by email, including a list of SciNet courses on scientific computing you took, to support@scinet.utoronto.ca.

Scientific Computing Course List

• Introduction to the Linux Shell (2 credit-hours)
• Modern Fortran (7 credit-hours)
• Scientific C++ (7 credit-hours)
• Scientfic Computing Course Part I – Software Development (12 credit-hours)
• Scientfic Computing Course Part II – Numerical Tools for Physical Scientists (12 credit-hours)
• Profiling and Performance Tuning (3 credit-hours)
• SciNet Developer Seminars (1 credit-hour each)

The latest version of this list can be found on the wiki: http://wiki.scinethpc.ca/wiki/index.php/SciNet_Certificate_Program.

Certificate in High Performance Computing

High Performance Computing, or supercomputing, is using the largest available computers to tackle big problems that would otherwise be intractable. Such computational power is needed is a wide range of fields, from bioinformatics to astronomy, and big data analytics. Since the largest available computers have a parallel architecture, using and programming high performance computing applications requires a specialized skill level.

This certificate indicates that the holder has successfully completed at least 36 credit-hours of coursework in high performance computing topics such as programming models like OpenMP, MPI, CUDA or parallel development tools like debuggers.

Requirements

• A total of 36 credit-hours or more from the list of SciNet courses on high performance computing given below.
• Upon completion of your certificate requirements, you must request your certificate by email, including a list of SciNet courses on high performance computing you took, to support@scinet.utoronto.ca.

High Performance Computing Course List

• Intro to Scinet (1 credit-hour)
• Five-day Practical Parallel Programming (up to 32 credit-hours)
• Scientific Computing Course Part III – High Performance Computing (12 credit-hours)
• Parallel I/O (3 credit-hours)
• Ontario HPC Summerschool (up to 24 credit-hours)
• Introduction to GPGPU with CUDA (7 credit-hours)
• Minicourse: Intro to GPU with CUDA (12 credit-hours)
• Parallel debugging (7 credit-hours)

The latest version of this list can be found on the wiki: http://wiki.scinethpc.ca/wiki/index.php/SciNet_Certificate_Program.

May 13, 2013

Come work for us at SciNet, helping solve the biggest computing problems in Canadian Research!

Applications are due May 6^th.

Under general direction, the SciNet Applications Analyst provides senior IT services in parallel programming for the SciNet High Performance Computing (HPC) consortium which serves researchers at the University of Toronto including faculty, postdoctoral fellows and graduate students in all disciplines and fields (e.g. science and engineering, finance, languages, etc.). The incumbent will be involved in “massively-parallel computing” with the task of running single jobs that simultaneously make use of up to 30,000 cores. S/he will also work with researchers and research teams to plan, develop, install and optimize the initial SciNet systems for various research programs and will provide technical consultation to researchers on their system needs for research operations. SciNet operates the two largest High Performance Computing (HPC) systems in Canada and provides HPC resources and support to researchers at the University of Toronto, the affiliated research hospitals and other Canadian universities.

To find out more and apply, go to https://utoronto.taleo.net/careersection/10000/jobdetail.ftl?lang=en&job=1300283

The ideal candidate will be able to combine theoretical and experimental work on modeling, optimization, design, fabrication and testing of electrochemical sensors using low-cost technologies.

Eligible candidates must have a broad set of skills, including:

• Programming skills in a high-performance computing environment.
• Experience on modeling and optimization of sensors for water quality monitoring.
• Experience in the design, fabrication and testing of sensors using low-cost technologies such as ink-jet printing or mainstream compatible semiconductor technology.
• Knowledge of wireless technologies to be integrated with sensors and used to continuously monitor drinking and waste water systems autonomously.

Required:

• Ph.D. in Electrical Engineering, Computer Engineering, Physics or Chemistry or other related fields.
• Doctorate degree must have been received within the past 10 years.
• English: Fluent with good ability to communicate orally and in writing.

For more information and to apply, go to http://jobview.monster.com/Sensor-Technology-Specialist-Job-Toronto-ON-CA-121599884.aspx

The format will be a four-day workshop with mixed lectures and hands-on sessions on a number of selected subjects, including shared memory programming, distributed memory programming and general purpose graphics processing unit programming. The graphics cards and distributed memory sessions will be given in parallel.

SESSIONS

• Linux command line: a primer
• Introduction to High Performance Computing
• Shared memory programming with OpenMP
• Distributed memory programming with MPI
• General Purpose GPU Programming with CUDA
• HPC Debugging
• HPC best practices
• Visualization

LOCATION

This event will be held in Sidney Smith Hall, University of
Toronto, 100 St. George Street, Toronto, Ontario M5S 1A1.

CERTIFICATE

Participants that complete at least three days worth of instruction will be given an Ontario Summerschool Certificate. Note that this certificate is separate from the SciNet certificates.

MORE INFORMATION AND REGISTRATION

For more information and (free) registration, please go to

http://ss2013-central.sharcnet.ca/

The SciNet Team

Dworkin and his team of six graduate students use SciNet to run complex simulations that measure combustion chemistry, particle diffusion, fuel temperature, pressure, and a host of other variables.
With rapid industrialization in developing nations like China and India, Dworkin’s research could have a profound influence on climate change and pollution-borne illness.

Read more at The Eye-Opener

Role and Responsibilities

Monitor and respond to HPC user requests in a timely and accurate manner: e.g., account creation, software installation, troubleshooting jobs, disk quota allocations

Configure and manage a Sun Grid Engine job management environment by creating/updating queues, variables, resources

Ensure that all tasks performed maintain the performance, security and reliability of the systems
Work with monitoring tools and log files to proactively identify problems and take action to avoid service interruptions, and to reduce down time when service disruptions occur

Perform operating system, firmware, software installations and upgrades on compute nodes and file systems

Follow best practices procedures and methodologies associated with supporting and operating complex information technology infrastructures including change management and problem management

Maintain and update documentation

Assist the IT Help Desk team with HPC user support issues

Perform data backup and restore tasks

Participate in the System Administration of non-HPC Research IT infrastructure

The HPC Systems Administrator will participate in an on-call rotation for providing after hours/weekend support and is required to work occasionally after hours/weekends

For more information, follow this link.

As a key member of the team, this position is mainly responsible for the invention of innovative image processing and image-based rendering algorithms. This position is also responsible for the continuous improvement of existing technologies developed by the group and for the protection of proprietary intellectual property created through in-house R&D programs.

Key Responsibilities:
Research and create innovative methods and algorithms that achieve “state of the art” performance in capture, enhancement, and display of very high-quality images.
Committed to R&D project plan and complete R&D project milestones on schedule and on budget.
Provide expert advice to in-house product development and motion picture production projects.
Document research results and submit progress reports on a regular basis.
Participate actively in patent creation and submission to protect proprietary IP.
Desired Skills & Experience

Requirements:
A Ph.D or other post-graduate degree in the fields of digital image processing, video processing, computer graphics, computer vision, or another closely related area.
Expert knowledge of the latest academic and industrial advances in motion image processing, computer graphics and computer vision. Research experience in temporal processing, image segmentation and texture synthesis is an exceptional asset.
Knowledge of the basics of human visual perception including colour science.
Strong experience and skills in at least one of the programming languages C, C++, C#, or Matlab.
At least 5 years of experience in research and development, preferably for real-world applications including motion pictures, television and video, or other areas dependent upon digital image processing technologies.
Experience and knowledge of current digital cinema projection technology or current digital cinema camera technology is a valuable asset.
Experience and knowledge of the motion picture and video post-production environment and standards is a valuable asset.
Experience in real-time image processing using GPU or FPGA/ASIC is a valuable asset
Demonstrate a proven track record of successful completion of research projects and product delivery.
Demonstrate strong motivation for achieving excellence and a high quality standard for one’s work.
Strong research ability and problem solving skills.
Strong analytical ability and mathematical skills.
Proven ability for innovation and risk-taking.
Proven ability to work independently and to deliver results with minimal supervision.
Proven ability to work well as part of a team.
Thrive in a high pressure and deadline oriented environment.
Fluency in both Windows and Linux operating system environments.
Good verbal and written communications skills.

For consideration, please apply online. We thank all applicants for their interest in IMAX but only those selected for interview will be contacted.

IMAX is an Equal Opportunity Employer.

The ideal candidate must have extensive scientific computing skills and deep knowledge of light-matter interaction.

Eligible candidates must have a broad set of skills, including:
Experience in formulating numerical schemes for solving Maxwells equations
Experience in designing, coding and documenting software to implement numerical schemes
Experience with finite differences, finite elements, moment methods and/or Greens functions
A deep understanding of nonlinear optics and nanophotonics is an asset (?)

Required:
Ph.D. in Physics, Electrical Engineering, or Engineering Physics or other related fields
Doctorate degree must have been received within the past 5 years
Fluency in English (written and spoken)

Preferred:
Engineering or physics background
Capable of working independently and within a team, self-motivated
Knowledge of parallel-processing computer platforms

Job Responsibilities:
Help the investigators at the University of Ottawa with the development of finite-difference time-domain methods for modelling electromagnetic phenomena on a massively parallel computing platform (BlueGene)
Primary responsibility for formulating implementing and running the code
Work with research partners to model specific structures of interest such biological tissues and plasmonic nano-antenna arrays
Produce appropriate documentation on the code
Assist in the dissemination of results to the community at large via journal publications or other suitable venues

Work Location:
University of Ottawa, Ottawa, Ontario

Term of Contract:
2-years maximum.

For more information and to apply, follow this link.

Job Status: Open
Start Date: Apr 1, 2013 End Date: Apr 1, 2014
Description: S.i. Systems on behalf of our valued client is seeking an experienced Fortran Developer with experience in mathematical/scientific modeling for a contract engagement in Ottawa.

As the successful candidate you will have significant experience developing and coding with Fortran.
Specialization and Skills:
Software Development application developer 5 – 7 years
Additional Requirements: Must have a minimum of three years developing with Fortran (Mandatory)
Must hold a minimum of Enhanced clearance (Mandatory)
Work Environment: One year contract with the possiblity of further extensions. Ottawa location.

Apply for the job here.

The 27th annual High Performance Computing Symposium, HPCS 2013, “Big Compute + Big Data = Big Insights”, is being held June 2-6 in Ottawa. The conference is being organized by the Ontario HPC Consortia – SciNet, SHARCNET, and HPCVL.

Registration for the conference is now open, with early bird  discounts available ( http://2013.hpcs.ca/registration ); and you still have until May 17th to submit abstracts Work-In-Progress posters to the conference on HPC topics ( http://2013.hpcs.ca/2nd-call-for-submissions/ ).

We look forward to seeing you in Ottawa!

The SciNet Team