Dear applicant!

Thank you for your interest in ADVANCE Research Grants.

We wish you good luck and look forward to getting to know you through your application.

Should you have any questions, please contact FAST at programs@fast.foundation. 

The 'Novel deep neural networks for inspection of solar panel anomalies using multimodal images/videos' is a 4-year research project to be conducted under the supervision of Prof. Sos Agaian, professor at City University of New York.

The project will significantly impact the development of AI technology with application in Armenia.

• Extend knowledge on creating solar panels' multimodal-multi camera analysis and management systems.
  

• Generate new knowledge and information about special damages caused to solar panels by Armenia’s climate, dust, and wind.
  

• Better understand the complexities of renewable PV energy sources. Gain large-scale knowledge about deep neural networks for detection, localization, and classification of solar panel damages using multimodal images/videos.
  

• Deliver baseline data for subsequent targeted studies using more specialized sampling and study designs such as mark/recapture and patch occupancy.
  

• Learn how to use known databases, generate so-called Armenian baseline/relevant data and information, and identify the gaps to run such models for Armenia.
  

• Increase practical experience in creating novel machine learning modules, including transformers and a few-shot learning system.
  

• Transform the developed technology and database accurately and inexpensively, and catalyze many fields of ecology, renewable PV energy, global warming, and carbon dioxide emission into "big data" sciences.
  

• Publish several research papers in international top machine learning and computer vision journals.
  

The research project is hosted at Yerevan State University.

The Discovery of New Drug Targets and First-in-class Chemical Modulators: from Diverse 3D-AI data to Leads is a 4-year research project to be conducted under the supervision of Prof. Rugen Abagyan from University of San Diego, Skaggs School of Pharmacy and Pharmaceutical Sciences.

The goal of the project is to target new emerging biological pathways essential for diseases that are currently poorly treatable. Within the research project, it is expected to develop a powerful pipeline, tools, and computational models to perform efficient screens against billions of chemical compounds to identify a small number of drug candidates. These drug candidates will be tested in disease-relevant experimental assays to select a preclinical candidate with a perfect pharmacological profile, including efficacy, selectivity, distribution, and minimal adverse effects to address emerging healthcare challenges.

The research project will be hosted at the Orbeli Institute of Physiology of National Academy of Sciences of Armenia. 

To be eligible for the research project, the applicant is expected to meet the following requirements:

• have obtained or be in the process of obtaining a master's degree in Mathematics, Molecular Biology, Data Science, Medicinal Chemistry, Drug Discovery, Biology.
  

• have experience in large-scale computing, data analysis, AI, and Machine learning models or be familiar with Molecular and Cell-based activity assays, compound screening.
  

• have good command of English language.
  

• have good communication and presentation skills.
  

• have at least part-time commitment to project per week, including participation in weekly online team meetings.
  

• be willing to travel abroad for presentations and participation in conferences and workshops.
  

Please note applications are accepted on a rolling basis.