About Us


mSemicon has a paid internship position open for recently graduated engineers or those in their final years of study.

The role

This position is being offered as part of the Horizon 2020 Auto-DAN project in which mSemicon is currently participating.

The objective of the student will be to perform a feasibility study on Machine Learning (ML) algorithms and then to demonstrate how these can help with the development of a gas boiler monitor and a smart IoT electricity meter.  

The student will also develop, together with mSemicon engineers, the algorithm and then test it in real-life situations.

At the end of the traineeship, the student will have acquired new practical skills and have enough material for publication and/or a thesis.

Skills required

  • Background in Embedded Systems Engineering 
  • Knowledge of Machine Learning algorithms 
  • Willing to relocate to Dublin, Ireland 
  • Experience in software programming languages such as Python, C or Arduino 
  • Professional written and spoken English 
  • Results-oriented 
  • A humble learner and quick study 
  • Able to work as part of a team


  • Experience in development with ESP32 platform 
  • Experience in developing ML algorithm for embedded systems 
  • Ability to write technical documents 
  • Experience with TensorFlow and Neural Networks


The student will be responsible for conducting a feasibility study regarding the implementation of ML algorithms into embedded systems for IoT applications and survey the best algorithms to be used for the given application. 

The student will collect data and perform a data analysis with the best ML algorithm. 


The traineeship will have a duration of at least 6 months with the possibility of extension if necessary.

A nominal stipend will be offered for this position.


mSemicon welcomes enquiries and applications at the company's email address.

Please note that applications for Erasmus+ registration and support are the responsibility of the applicant.

This position is also available to suitable candidates, independently of the Erasmus+ program. Partial remote working is an option.

Issued: 14.01.2022