Internship in Machine Learning in Zug

The Auto-Identification team is a divisional Competence Center. It provides a maintained portfolio of standardized and validated auto identification devices enabling each sample, reagent and disposable in any of DIA instruments and solutions to be identified securely, reliably, and consistently. Our consulting services and devices allow for fast integration and maintenance of auto-identification functionality in DIA instruments

As an Intern in the Auto-Identification team you will work on measuring the performance of different Machine Learning techniques for the identification of tube and cap types used in selected instruments.

Your main tasks would include:

• Assessing the different architectures for image based machine learning solutions, including the hardware and software components (industrial camera, smart camera, commercial and open source software.)
• Setting-up your development and test environment
• Exploring the different machine learning techniques for tube and caps identifications. The image library for training and test will be provided.​​
• For each algorithm, assess the influence of the training set and the impact of the number of categories ​
• Documenting and presenting the results

Ideally, you fulfill the following criteria:

• You are currently enrolled in a Bachelor's or Master's degree program or have completed it up to a maximum of 12 months ago (Electrical Engineering, Computer Science, Physics)
• Experience in working with embedded systems
• Good knowledge of image processing
• Strong hands-on experience in state-of-art Machine Learning techniques.
• General prototyping skills using MATLAB, Python or other equivalent development tools
• Excellent spoken and written English

Start date: February or March 2019

Workload: 100%

Duration: 6 months

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Tags: ROiEE, ROiPT, ROiTEC, ROiDS, ROiDIG, ROiCS, ROiSENG

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