Developing a model for a Data Lab for Science linking with EOSC and RAISE (RAISE pilot) (CSA)

1. %42
   SERDAR DURDAĞI

   ProfesörBahçeşehir Üniversitesi

   Shared topics: Machine Learning in Materials Science

   Overlapping papers: Exploring the binding capacity of lactic acid bacteria derived bacteriocins against RBD of SARS-CoV-2 Omicron variant by molecular simulations (2023) · Rapid and efficient ambient temperature X-ray crystal structure determination at Turkish Light Source (2023)

2. %42
   TEMEL KAAN EKİZ

   Araştırma GörevlisiBiruni Üniversitesi

   Research topics: Software Engineering Research · Mobile Crowdsensing and Crowdsourcing · Machine Learning and Data Classification

3. %40
   MERVE ARITÜRK TÜREN

   Araştırma GörevlisiBahçeşehir Üniversitesi

   Research topics: Robotic Path Planning Algorithms · Social Robot Interaction and HRI · Evacuation and Crowd Dynamics

The fit is computed by code on every request. The call text (title, keywords, start of the official description) is compared with three sources: semantic similarity to the academic profile (50%), shared distinctive terms in YÖKSİS keywords and OpenAlex topics (25%) and publication content — titles, English abstracts and their Turkish translations (25%). Thanks to the translations, Turkish calls also meet papers written in English. Common words weigh little; below 40% is not shown. A subject hint only — not an eligibility, capacity or merit assessment. Hidden profiles are never listed.