Artificial Optical Inspection - AI from sorting to soldering Internship

For our OSIE project, Nexedi is looking for a trainee whose task is to implement tow Artificial Optical Inspection (AOI) models. You will start developing and implementing a model for sorting good and bad fruits in order to become familiar with our stack before you will work on the same stack to create a model for evaluating soldering joints on motherboards of small computers and routers.

AOI has multiple purposes:
- detect quality problems: meaning rotten/misformed fruits and later bad soldering or missing part in a package;
- detect logistic attacks: probably not in fruits... but on a motherboard, this means evaluating whether components were added to the original PCB layout design.

AOI is based on various techniques of vision, including - but not only - machine learning (scikit-image, scikit-learn, etc.). A Wendelin data-lake is involved to collect large sets of images. Data Sets will be published as open data.

The traineeship will teach you how to develop a model and implement in our test production line. Afterwards you will work on micro-servers produced by Olimex, the world's largest designer of open source hardware. All PCB layouts of Olimex are available under open source licenses and are designed using KiCAD open source PCB design software. Olimex is based on Bulgaria in the city of Plovdiv.

Opportunities
- Master artificial optical inspection (AOI)
- Master anomaly detection
- Master PCB quality assurance
- Master Edge Computing based on SlapOS
- Master Olimex open source hardware

Responsibilities
- Contribute to data science and vision algorithms for PCB quality assurance
- Contribute to open source projects: scikit-learn, scikit-image, Wendelin, etc.
- Contribute to Edge Computing projects for industry-leading clients
- Contribute to research projects to build the future of our open source stack

Requirements
- Passionate, self-driven.
- Willingness to contribute to an open source ecosystem and the Free Software community.
- Good skills in GNU/Linux operating system.
- Good programming skills in python.
- Basic knowledge of data sciences, applied mathematics and vision algorithms.
- Good software development skills (version control, testing, debugging).
- Good command of English.