The application deadline for Insight’s Fall Fellowships is quickly approaching on July 9th, so I want to pass along the latest information about our upcoming sessions.
The Insight Data Fellows Programs are tuition-free fellowships for graduating students, PhDs, and postdocs looking to transition to careers in fields like data science, data engineering, artificial intelligence, and many others. Over the past 6 years, we have helped over 1400 Insight Fellows become data scientists and engineers at over 250 leading data-driven companies.
We have received a number of applications from CERN in the past, and several alumni have gone through our program, including Michel Trottier-McDonald who is now at Twitter.
Head of Admissions
Insight Data Science
Insight Data Fellows Programs
Insight is now accepting applications from graduating students for our fellowships in:
– Data Science (for PhDs & Postdocs)
– Health Data Science (for PhDs & Postdocs)
– Data Engineering (for Bachelors, Masters, or PhDs)
– Artificial Intelligence (for Bachelors, Masters, or PhDs)
– Data Product Management (for Bachelors, Masters, or PhDs)
– DevOps (for Bachelors, Masters, or PhDs)
1400+ Insight alumni are now working at Facebook, LinkedIn, The New York Times, Apple, Airbnb, Netflix, Memorial Sloan Kettering Cancer Center, Github, Slack, 23andMe, Twitter, Bloomberg, NBC, Pinterest, Microsoft, and 250+ other top companies.
Insight Fellows Programs:
– 7 week, full-time training fellowship
– Mentorship from leading industry data scientists, data engineers & AI specialists
– Join an active community of Insight alumni
– Self-directed, project-based learning followed by interviews at top companies
– Tuition-free with need-based scholarships and loans available to help cover living costs
Upcoming Early Application Deadline: July 9
Learn more & apply on our website: https://www.insightdatascience.com/apply
Not ready to apply? Sign up for our notification list: https://www.insightdatascience.com/notify
Questions? Email us at firstname.lastname@example.org
The 2018 Smoky Mountains Computational Sciences and Engineering Conference (SMC18) is currently accepting teams to participate in its 2nd Annual Data Challenge. This contest is open to
students, faculty, and industry professionals who are interested in performing novel analysis on real scientific data sets. Teams of one to four people may participate.
ORNL data sponsors will provide teams with actual scientific data sets to explore 3 to 5 related challenge questions. The challenge questions for each data set will cover multiple difficulty levels, with the first question in each challenge being suitable for a novice, and each question thereafter increasing in difficultly,
with the series of questions ending with an advanced/expert level challenge question. The top teams will be invited to attend SMC18 in Gatlinburg, TN, where they will present their work and the winner will be crowned. Registration is open until June 22 and the competition ends July 31 (submissions are due by 5:00 PM Eastern on July 31).
The Data Challenge is intended to draw scientists and researchers who may be at the beginning stages of incorporating data analytics into their workflow, to data analytics experts who are interested in applying novel techniques to data sets of national importance.
To register, or for more information, visit the Data Challenge
website at https://smc-datachallenge.ornl.gov.
Applications Open for GPU Hackathon at Brookhaven National Laboratory, September 17-21, 2018
Brookhaven National Laboratory will host its 2nd GPU Hackathon on September 17-21, 2018. The Hackathon will bring together domain scientists, computational scientists, tools developers and hardware vendors to accelerate scientific codes on GPUs through the 5-day intense hands-on training. Team applications are being accepted until June 30, 2018. For more details, go tohttps://www.bnl.gov/gpuhackathon2018
INTRO TO HPC TRAINING (JUN 26-28)
The OLCF will host an Introduction to High Performance Computing (HPC) workshop on June 26-28, 2018. This training will start by covering basic skills, such as UNIX, vim text editor, and c/Fortran programming, which will be necessary for the topics to follow. We will then move on to cover basic parallel programming (using MPI and OpenMP) and GPU computing (CUDA and OpenACC). Hands-on sessions will be included with many of the topics to give participants the opportunity to practice new skills. For more information about this event or to register,
The OLCF will present an Introduction to Summit webinar from
1:00 PM until 4:30 PM (Eastern Time) on Friday, June 1. In this
webinar, we will cover the basic topics new users will need to
get up and running on Summit. We will give a broad overview of
available features and the details necessary to submit and run
jobs. For more information, please see the event page at
The HEP-CCE announces the Scalable IO Workshop at Argonne National Laboratory
23-24 August 2018
High Energy Physics experiments continue to become more data and simulation intensive. There is an expected factor of ten (or more) gap between projected computing needs for HL-LHC experiments and projected growth of current HEP resources. In the US, High Performance Computing resources are going to be growing by more than an order of magnitude by 2021/2022 with the deployment of the US DOE’s first exascale supercomputers. These resources are already becoming an important piece of the HEP computing landscape and will continue to become more important.
One challenge of using leadership computing resources is reading and writing data in scalable ways that does not lead to bottlenecks or performance penalties on the shared filesystems. This Workshop aims to bring together leading IO experts in the HEP field with experts from DOE ASCR Facilities to discuss how to move forward in the next years to make HEP software more friendly to millions of parallel threads accessing files on shared disks.
On February 26-March 2, 2018, Brookhaven National Laboratory (BNL) hosted a hackathon targeting the Intel Xeon Phi (formerly code-named Knights Landing, or KNL) processors for scientists to come together to optimize their application code performance on the KNL-based supercomputers. Out of the five teams who participated, two teams came from the high energy physics community:
- APES (Accelerator Particle Energy Simulator): A code for tracking particle-device and particle-particle interactions that has the potential to be used as the design platform for future particle accelerators. Team members all came from BNL.
- ART: a code for simulating the formation of structures in the universe, particularly galaxy clusters. Team members came from Yale University and University of Miami.
Each team was paired with a mentor with similar scientific background. They also had access to four floating mentors from Intel who brought expertise in OpenMP, Intel hardware architectures, compilers and performance profiling tools. The teams worked with their mentors for five days in a hands-on setting. By the end of the week, all teams achieved significant performance improvements for their codes, with ART and APES achieving >2X and >5X speedup, respectively.
Held at the ALCF from May 15–17, our intensive three-day workshop is aimed at experienced HPC users with goals of applying for a major allocation award.
Carnegie Mellon University (CMU) and Georgia Tech (GT) will be hosting a
3-day conference on “Machine Learning in Science and Engineering” on
CMU’s campus in Pittsburgh on June 6-8, 2018. The purpose of the
conference is to bring together researchers across the disciplines to
present the latest ideas on the applications of ML methods in their
fields as well as providing a forum for work on the development of new
algorithms designed for challenges in science and engineering. More
information on the conference can be found at the website
Together with Deirdre Shoemaker from Georgia Tech, I am co-chairing the
Physics Track of the conference. We invite you all to submit abstracts
for 15+5 minute contributed talks through your respective collaborations
that have received information about abstract contributions to our ML
In case of any questions, please contact email@example.com
Two days of KNL training and optimization sessions being held at NERSC March 6 and 7th.
The training will be presented by Intel experts covering Intel compilers, optimization tools, and libraries and will take place on Tuesday, March 6, 2018.
The following day, there will be a KNL hack-a-thon, with Intel and NERSC experts on hand to help you evaluate the performance of your application and develop an optimization strategy.
The events will be held at LBL’s Shyh Wang Hall (Building 59, CRT) in Room 3101. All sessions will presented online using Zoom but we highly recommend attending in-person if you can.
See https://www.nersc.gov/users/training/events/intel-compilers-tools-and-libraries-training-march-6-2018/ and https://www.nersc.gov/users/training/events/cori-knl-hackathon-march-7-2018/ for details and registration.
Please register for both days if you plan to attend either in person or remotely.