English

TMA Tech Group is a leading technology group in Vietnam with 27 years of development, more than 4,000 talented engineers, clients in over 30 countries, and 16 years of winning the Gold Medal for software export.

 

Currently, TMA Tech Group is looking for potential candidates for the Internship Program in August 2024 for students. Detailed information is in the poster below.

Positions: 

  • AI Engineer
  • Data Engineer
  • Back-end Developer (Java, Python, .Net, NodeJS)
  • Embedded Engineer (C++)
  • Mobile Developer (Flutter, iOS, Swift)
  • Front-end Developer (ReactJS, Angular)
  • Automation Tester
  • Business Analyst
  • Business Development
  • UX/UI Designer

Requirements : 

  • Students from the end of their 3rd year
  • Minimum internship duration of 3 months starting from August 2024
  • GPA >= 7.0

Benerfits:  

  • Opportunity for part-time contracts with salary
  • Direct guidance from Subject Matter Experts (SME)
  • Training in advanced technology and basic working skills
  • Provided with necessary working equipment

Application Documents:

  • English CV
  • TOEIC or IELTS certificate (if available)
  • Latest academic transcript with confirmation from the university (soft copy)

Submit applications to: This email address is being protected from spambots. You need JavaScript enabled to view it.

Application deadline: 15/08/2024

Contact Information: Industry Internship

  • TMA Building, No. 10, Quang Trung Software City, Tan Chanh Hiep Ward, District 12, HCMC
  • Phone: 028 3997 8000 - Ext: 5615 / 028 3891 2532
  • Email: This email address is being protected from spambots. You need JavaScript enabled to view it.

 

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Lectures by Thomas Koberda

June 20, 2024, Room 207, 227 Nguyen Van Cu, District 5, HCMC

Thomas Koberda is a professor of mathematics at the University of Virginia, USA. He has given lectures at our faculty several times and has mentored several students in Vietnam during past few years.

  1. Program
  • 9:00–11:00: Gromov–Hausdorff Convergence, Thomas Koberda

  • 13:30–14:15: Introducing programs on mentorship and  REU (Reseach Experience for Undergraduate), Thomas Koberda

  • 14:15–15:45: Short presentations by former student participants of the above programs, Nguyễn Hoàng Khang, Đỗ Hoàng Việt, Liêu Long Hồ, Hồ Nguyễn Huyền Thư

The students, master’s students and Ph.D. students and anyone interested are invited to participate in the meeting. To attend, please register (scan the QR code below or click on the link).

PIC

"Probability - Statistics Seminar in January 2024" is going to be organized with a report by Dr. Nguyen Hung Minh Tan.

Dr. Tan Nguyen is currently an Assistant Professor of Mathematics (Presidential Young Professor) at the National University of Singapore (NUS). Before joining NUS, he was a postdoctoral scholar in the Department of Mathematics at the University of California, Los Angeles, working with Dr. Stanley J. Osher. He obtained his Ph.D. in Machine Learning from Rice University, where he was advised by Dr. Richard G. Baraniuk. Dr. Nguyen is an organizer of the 1st Workshop on Integration of Deep Neural Models and Differential Equations at ICLR 2020. He also had two awesome long internships with Amazon AI and NVIDIA Research. He is the recipient of the prestigious Computing Innovation Postdoctoral Fellowship (CIFellows) from the Computing Research Association (CRA), the NSF Graduate Research Fellowship, and the IGERT Neuroengineering Traineeship. He received his M.S. and B.S. in Electrical and Computer Engineering from Rice University in May 2018 and May 2014, respectively.

Undergraduate, Master and Ph.D. students and interested people are invited to participate the seminar.

    • Time:  09:30 a.m. Wendsday, June 26, 2024.
    • Location: Room E202B, Campus 1- University of Science (227 Nguyen Van Cu St., District 5, Ho Chi Minh City).

Title: Principled Frameworks for Designing Deep Learning Models: Efficiency, Expressivity, and Robustness

Summary of the report is as follows:

Designing deep learning models for practical applications, including those in computer vision, natural language processing, and mathematical modeling, is an art that often involves an expensive search over candidate architectures. In this talk, the speaker will introduce two novel optimization frameworks to facilitate the process of designing efficient and expressive deep learning models including the neural ordinary differential equations (Neural ODEs) and transformers.
 

Scan the QR code below or click on the link before June 25, 2024 to register to attend.

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  1. Invited Speaker: LAM HOANG NGUYEN (School of Science and the Environment, Memorial University of Newfoundland, Canada, https://sites.google.com/view/nguyenlammath/cv)

  2. Date & Time: 30, May, 2024, 09.30 a.m -11.00 a.m.
    Venue: Room F207, Campus 1- University of Science(227 Nguyen Van Cu St., District 5, Ho Chi Minh City).

  3. Title: Hardy-Rellich type inequalities: A new approach and symmetrization principle.

  4. Abstract: We present a new way to use the notion of Bessel pair to establish the optimal Hardy-Rellich type inequalities. We also talk about necessary and sufficient conditions on the weights for the Hardy-Rellich
    inequalities to hold. Symmetry properties of the Rellich type and Hardy- Rellich type inequalities will also be discussed. The talk is based on joint work with Anh Do, Guozhen Lu, and Lu Zhang.

  5. Organizer: KIM HA, LY (Vietnam National University – Ho Chi Minh City, University of Science)

After the seminar, Professor Nguyen will also introduce the graduate program and scholarships at School of Science and the Environment, Memorial University of Newfoundland, Canada.