Discovering the Future
Unprecedented platform to bring the top-notch expertise in the targeted STEM-related fields in Armenia
General Information
About the program

The ADVANCE STEM Research grant program sets ground for development of scientific directions in STEM-related fields in Armenia. This pioneering platform invites distinguished scientists from all around the world to lead new teams comprised of ambitious Armenian researchers. The experience and network these emerging Armenian researchers gain in the program boosts their professional growth, enables effective global collaboration, and significantly increases research output in target fields. The comprehensive financial and logistical support provided by FAST and its partners works toward putting Armenia on the map of cutting-edge scientific research worldwide.

We provide 2 to 4-year grants to the research groups formed in Armenia around a project proposed and led by a distinguished scientist from abroad called an international Principal Investigator (PI).

Aiming to foster inter-institutional and interdisciplinary connections, we put together diverse and multi-faceted research groups, where there is a lot to learn from each other. We encourage qualified and motivated researchers from any institution in Armenia and beyond to apply. You can find out more about our projects and open calls in the “Research Projects” section.

The research is conducted primarily in Armenia. The PIs both visit Armenia and supervise the group’s work remotely. The PIs also teach at local universities, helping to nurture aspiring researchers in relevant fields of study.

About the Principal Investigators

The international PIs are scientists with solid expertise in a related field, extensive experience in leading groups of researchers, and strong ties to the global scientific network. The PIs submit the project proposal, introducing their vision for the project’s development and the scientific field’s development in Armenia overall. They also define the needs of the proposed project and requirements for the researchers, participate in the selection of the researchers, and ensure the quality of the research output produced in the scope of the project.

Qualified specialists are invited to submit an online application to be considered for the role of an international PI.

Granting scheme

The grant includes the following budget lines:

  • PI’s travel expenses and coverage of expenses during their visit to Armenia,

  • Salaries for the local researchers,

  • International travel costs for the local researchers’ participation in the conferences, collaborative research activities abroad, or other capacity-building events,

  • Laboratory materials, consumables,

  • Publications in journals and, if applicable, patenting costs.

PIs engaged
local researchers funded
intensive courses organized
Dr. Garabed Antranikian
Principal Investigator (PI), Biotechnology Project
Dr. Hovik Panosyan
Expert, Biotechnology Project
Dr. Anna Poladyan
Senior Researcher, Biotechnology Project
Dr. Sargis Aghayan
Senior Researcher, Biotechnology Project
Dr. Karen Trchunyan
Senior Researcher, Biotechnology Project
Dr. Ani Paloyan
Senior Researcher, Biotechnology Project
Ms. Ella Minasyan
Junior Researcher, Biotechnology Project
Ms. Diana Ghevondyan
Junior Researcher, Biotechnology Project
Dr. Arnak Dalalyan
Principal Investigator (PI), Machine Learning Project
Dr. Arshak Minasyan
Senior Researcher, Machine Learning Project
Ms. Sona Hunanyan
Senior Researcher, Machine Learning Project
Mr. Tigran Galstyan
Junior Researcher, Machine Learning Project
Mr. Henrik Sergoyan
MSc. Student, Machine Learning Project
Mr. Khachatur Khechoyan
MSc. Student, Machine Learning Project
Research projects
Statistical Analysis of Machine Learning Algorithms (SAM-lab)

Title: Statistical Analysis of Machine Learning Algorithms (SAM-lab)

Principal Investigator: Prof. Arnak Dalalyan

University: ENSAE Paris, France

Research Team: Sona Hunanyan, Arshak Minasyan, Tigran Galstyan, Henrik Sergoyan, Khachatur Khechoyan

Vacancies: Senior Researcher

Monthly Remuneration: 1000 USD/30 hours a week

Duration: 2020 - 2024

Eligibility Criteria

To be eligible for the project, the applicant is expected to:

  • Have a Master’s degree in Mathematics/Applied Mathematics/Physics/Computer Science,
  • Have perfect knowledge of Linear Algebra, Analysis and Probability Theory,
  • Have some experience with R, Matlab or Python,
  • Have essential reading and writing skills in English,
  • Have experience of advanced research in some field of applied mathematics (applicable for the local coordinator only),
  • Be available at least 20 hours/week,
  • Have good writing and pedagogical skills (a plus).

Selection Process

Application packages are in the description of each project. The packages include the application form, CV, motivation statement, and recommendation letter(s). After reviewing the application packages, FAST shortlists eligible candidates for the PI’s review. The PI identifies those invited to the interview with the independent Evaluation Committee.

Project Importance

The current trend in Artificial Intelligence is to tackle most problems by statistical methods using Machine Learning algorithms. The progress needs to be backed by thorough mathematical analysis to understand the strengths and weaknesses of various methods and prepare solid ground for future innovations. Another trend of recent years is that the strongest students in mathematics and computer science are choosing to specialize in Machine Learning. Master’s programs in Machine Learning/Data Science/Artificial Intelligence are extremely popular all around the world. This is the case in Armenia as well, but the absence of a decent PhD program in this field forces best students to leave the country. One of the aims of this project is to create the possibility of getting a PhD in this field in Armenia.

Expected Results and Impact
  • Put Armenia on the map of cutting-edge research in Machine Learning and AI,
  • Publish an average of 4 research papers per year starting from the second year of the project,
  • Initiate several international collaborations by organizing a) PhD-level mini-courses taught by renowned researchers and b) an international workshop on Statistics and Machine Learning,
  • Foster collaborations with some potential local partners, such as PicsArt, Mentor Graphics, Krisp, etc.