Computer Engineers

İstanbul Bilgi Üniversitesi

We are looking for Computer Engineers researchers to work on a project carried out at İstanbul Bilgi University.

QUALIFICATIONS

Our research is primarily focused on developing an imaging system (both hardware and software) to detect health related body movements in real-time.

• Bachelor’s degree in Computer Engineering or related field,
• Strong development skills, with proficiency in Python,
• In-depth understanding of machine learning fundamentals and libraries libraries like PyTorch, TensorFlow, Numpy, Pandas, Gensim etc.
• Reading, understanding, and implementing scientific articles describing various ML/AI approaches applicable for our purposes,
• Develop state-of-the-art algorithms in one or all the following areas: deep learning, segmentation, object detection, image processing, activity recognition, anomaly detection, etc.
• Be familiar with infrared technologies, computer vision and image processing algorithms,
• Experience with REST API development, NoSQL design, RDBMS design and optimizations,
• Strong project/team management capabilities.

RESPONSIBILITIES

• Design and implement an embedded system together with optical imaging devices,
• Examine quantitatively the system quality and capability,
• Direct or coordinate manufacturing, installation, maintenance, support, and documentation to ensure compliance with specifications, maintaining project scopes, schedules, and budgets at all times,
• Prepare comprehensive documentation for all designs, including diagrams/schematics, bill of materials, assembly drawings, and design changes, test reports, design-validation plan, and reports to ensure that installation and operations conform to standards and requirements.

OBJECTIVES

• Creating an image data set by recording body movements,
• Labeling body movements using predefined constraints,
• Training different Convolutional Neural Networks (VGG, R-CNN, fast R-CNN, faster R-CNN etc.) and YOLO (real-time object detection) training on high performance computers and comparison of relevant models,
• Implementing a miniaturized imaging system which can monitor handwashing process in real-time,
• Testing and reporting the system within the scope of technology level in real environment.