Data Analyst Engineer for New Technology Applications
Data Analyst Engineer for New Technology Applications
Flanders Make
Leuven, Lommel or Kortrijk, Belgium
You use data analytics and machine learning techniques to predict machine behaviour and derive the optimal settings for robots, autonomous vehicles and industrial machines.
Use computing power for high-tech applications
Flanders Make research engineers are experts in developing new technologies for machines and vehicles. Automotive companies and machine builders in Flanders are looking for predictive control and data analytics to be able to take the next step in their innovation process.
- What if you could predict machine failure by analysing measurements?
- Why do certain automotive parts result in better performances than others?
For the development of high-tech machinery (e.g. compressor, 3D printer, self-guided robot, autonomous vehicle…), you will:
- Work together in a research team that combines expertise in artificial intelligence with expertise in the operation and control of machines and vehicles;
- Take the lead in developing predictive algorithms to process collected data and derive the optimal machine settings (Model-Based Data Analytics).
More concretely, you:
- Understand the goal of the measurement campaign and discuss how to gather relevant data with the team (e.g. temperature signals, accelerometer signals, energy measurements, failure signals…);
- Provide structure and insight into raw data;
- Find ways to process the flow of data;
- Use current data analytics methods as well as machine learning and deep learning techniques to search for relevant connections between input signals (e.g. which environmental factors could be influencing the energy efficiency of the machine?);
- Use and model predictive algorithms and interpret the results;
- Draw conclusions and suggest improved parameters to improve the performances or energy efficiency.
Statistical mind with passion for technology
You have:
- A Master or PhD degree in Engineering (Computer Science, Artificial Intelligence, Robotics…);
- At least 3 to 5 years of experience in an industrial or academic environment;
- Relevant experience with experimental designs for real-life (non-virtual) technology applications (machines, vehicles, robots...);
- Knowledge of or the ability to use a wide range of data analytics methods and machine learning (including but not limited to deep learning) and data wrangling techniques, e.g. random forests, support vector machines, and (convolutional/recurrent/deep) neural networks);
- Experience with at least one machine learning toolkit (Scikit-learn, Mahout, SparkML, Caffe, Tensorflow, R, KNIME, ...) and Matlab/Octave;
- Knowledge of one general-purpose programming language such as Java, C#, C++;
- A mathematical and statistical mind with a touch of “Data Intuition”;
- Communication and Data Visualisation skills are a plus.
You are:
- Passionate about the technology of machines and vehicles;
- Creative;
- A good communicator;
- An active listener who can build sustainable relationships.
Offer
- A challenging job, working with experts in various fields, using state-of-the-art infrastructure for eg. autonomous systems, machine & vehicle dynamics, predictive control, data analytics, software prototyping…;
- An open company culture with short communication lines;
- A multi-stakeholder research context;
- An enthusiastic, international team.
Flanders Make
Flanders Make is the strategic research centre for the manufacturing industry. From our sites in Kortrijk, Lommel, Leuven and Sint-Truiden, we stimulate open innovation through excellent research.
Our purpose: realising a top-level research network in Flanders that delivers full support to the innovation projects of manufacturing companies. In this way, we want to contribute to new products and production processes that help to realise the vehicles, machines and factories of the future.
How to apply?
To apply please use the Apply Now button below.
Please fill in the online application form and upload a motivation letter and cv.
