Pacific Northwest National Lab Info Session (Wednesday 10/19 @ 4:30pm)

You will learn about the types of job/research opportunities at PNNL, hear about the experiences of NCSU alumni who are currently working there, and speak with a recruiter directly!
Info Session: Pacific Northwest National Laboratories (PNNL)
Date: Wednesday, October 19, 2022, 4:30-5:30pm EDT
Location: SAS 4201

Sandia National Lab Info Session (October 18 @ 4:30 pm)

It is our pleasure to announce that SIAM will be hosting an info session with Sandia National Lab on Oct 18 at 4:30 pm in SAS 1216. There will be free food and giveaways!
Make a Difference: Mathematical Sciences R&D Careers at Sandia National Laboratories
R&D Staff from Sandia National Laboratories will be on campus recruiting top NCSU math and statistics students. With sites in NM and CA, SNL is a Department of Energy laboratory conducting wide-ranging science and engineering R&D supporting national security. Please join us for an info session and career fair! Students who register and submit a resume will be considered for one-on-one meetings to discuss their interests and possible careers at SNL.
Info Session: Make a Difference: Mathematical Sciences R&D Careers at Sandia National Laboratories
Date: Tuesday, October 18, 2022, 4:30p EDT
Location: SAS 1216
Free Food and Giveaways!
Abstract: Brian Adams (NCSU PhD 2005) will conduct a mathematics and statistics-specific information session including a brief overview of SNL’s mission, R&D areas, and opportunities in mathematics, statistics, and computational science. Staff and project profiles will demonstrate the ways you can contribute to high-impact problems in the national interest through fundamental math and computational science R&D, software/hardware development, and working in interdisciplinary teams on engineering applications. We are hiring at all degree levels.
Registration on Yello is encouraged and allows you to upload a resume and request a one-one-one career discussion with Brian. Please register on Yello to follow the registration link.
We are hiring Regular Staff (any degree), Post-Doctoral Researchers (PhD degrees), and Summer or Year-Round Interns (undergraduate or graduate). Many math, statistics, and computational science roles at SNL are officially “Computer Science R&D” and numerous intern and staff positions are open right now.
For more information about current job postings, please see SNL Careers, including in Computer Science and Cybersecurity. Also check out our Student Internship Institute Programs, particularly CSRI, NOMAD, and TITANS. You can set up a profile and register for notifications when your search criteria are met by new openings. US citizenship is required for positions that require security clearance or as stated specifically in the individual job posting.
Career Fair: We will also recruit graduate students at the NC MS/PhD Virtual Career Fair on Thu, Nov 3. Register via that link if interested.
Bio: Brian M. Adams is a principal member of technical staff in the optimization and uncertainty quantification department at Sandia National Laboratories, where he has worked since 2005.  He holds a PhD in Computational and Applied Mathematics from North Carolina State University.  Brian develops, implements, and applies algorithms for optimization and uncertainty quantification on computational models.  He leads the Dakota software project, managing software development and deployment to ensure impact on the span of Sandia science and engineering problems.

SIAM Bootcamp Series #2 – MATLAB (Sept 6 and Sept 13, 3-4pm)

The SIAM Student chapter is hosting another bootcamp: a two-part series that introduces you to MATLAB. Both graduate and undergrads are welcome, so please spread the word! You are encouraged to have Matlab installed, which is free for NCSU students. For a detailed instruction on how to download and install Matlab to your computer, please see this page.

As usual, drinks and light refreshments will be available to anyone who attends in person.

Speaker: Cole Butler and Burke King
Date/Time: Part 1 – Sept. 6 (Tuesday) 3-4 pm; Part 2 – Sept. 13 (Tuesday) 3-4 pm
Location: POE 211

Mathematics in Industry Seminar

The SIAM Student chapter will be hosting a Mathematics in Industry seminar at 3:00 PM on March 3, 2022 in Poe Hall 228. Our speaker will be Jared Cook.

Abstract: Jared finished his Ph.D. in Applied Math at NC State two years ago and since then has been working at Teledyne Technologies in their Intelligent Systems Lab. During that time he primarily worked on DARPA contracts, but also worked on internal research and development projects. He will be discussing his work on a power lines detection R&D project where he used computer vision to detect power lines in drone imagery. He has recently started a new position at MetLife as a Senior Research Scientist and will be answering questions about his former and new job as well as his experience job searching.

Mathematics in Industry Seminar

The SIAM Student Chapter will be having a Mathematics in Industry Seminar on January 27, 2022 at 3 PM in Poe Hall 218. Our speaker, David Padgett, is from a local defense contractor named Vadum will present on the company and different aspects of how machine learning and artificial intelligence algorithms can be used in national defense.

Abstract: Founded in 2004, Vadum delivers cutting-edge solutions to customers in the competitive field of national defense research and development. Vadum got its start developing innovative tools and techniques to protect personnel from improvised explosive devices used in Iraq and Afghanistan. Vadum has grown to tackle larger and more complex defense challenges in a range of mission areas and is now at the leading edge of technology development in areas such as electronic warfare and missile defense. Many of Vadum’s solutions employ machine learning and artificial intelligence algorithms to improve automatic inference and decision making. This talk will be both an overview of Vadum and an industry perspective on some of the technical and non-technical issues faced when applying ML/AI to real-world problems.