Computer Science Engineering

As a premier research institute, M.A.H.E. has been recognized with the esteemed title of "institute of eminence" since its establishment in 1953. M.A.H.E. has a rich history of pioneering education across various disciplines and has served as the alma mater for numerous successful individuals. The role involves delving into the realm of Unmanned Aerial Vehicles (UAVs) and their applications in remote sensing for both military and civilian purposes. With the recent advancements and price drops in UAV technology, these aerial platforms now boast advanced sensors and cameras that facilitate tasks such as object detection for surveillance, search and rescue operations, traffic monitoring, and military missions. However, challenges persist in aerial object detection, including variations in object scales, UAV jitter, camera orientation, lighting changes, and cluttered backgrounds. To surmount these challenges, this research role focuses on developing an efficient and accurate object detection algorithm for UAVs leveraging deep learning techniques. The primary objectives include enhancing aerial image quality through preprocessing techniques and devising a robust detection algorithm. The working hours for this position are from Monday to Friday, 9:00 am to 5:00 pm. Responsibilities: - Acquiring proficiency in computer vision applications utilizing deep learning. - Exploring advancements in UAV autonomy and sensor integration. - Tackling challenges related to object detection from aerial UAV footage. - Crafting deep learning algorithms for efficient object detection in UAVs. - Improving aerial image processing to enhance object localization. Eligibility: - Background in Computer Sciences (Required) Skills: - Proficiency in Computer skills (Required) - Strong Communication abilities (Required) - Effective Time Management skills (Required) - Critical Thinking capabilities (Required) - Proficient in Python programming language (Required) Languages: - Proficiency in English (Required) Nationality: - Open to candidates of Any Nationality Minimum Study Level: - Bachelor's degree (Required),