About Flanders Make
Towards a digitally transformed, sustainable and competitive industry
Flanders Make is a fast-growing research centre that performs research to support companies from various sectors in their sustainable innovation processes. From our establishments in Lommel, Leuven, Kortrijk and Sint-Truiden and labs within the 5 Flemish universities, we stimulate open innovation through excellent research.
Because of our unique position as a bridge between industry and research, our teams combine application and system proficiency with technological and scientific knowledge. Academic partners and more than 150 companies are part of the innovative circular ecosystem of Flanders Make.
Our strategy based on industrial needs and long-term trends ensures a close link with the industry and its challenges. With our programmed research, we create impact in companies.
Sustainability, climate and workability have a high priority in our research. We want to help companies in developing sustainable, green, smart and connected products and production systems, with a special focus on people and their interaction with machines.
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.
- 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
Please apply with your CV and cover letter by the 'apply' button below
Remember - you found this opportunity on Qreer.com
CAE / CAD / CAA
10 - 15 years
2 - 5 years
5 - 10 Years
|Job Location:||Lommel, Belgium|
|Keywords:||MACHINE LEARNING - ARTIFICIAL INTELLIGENCE - Model-Based DATA ANALYTICS - TENSORFLOW - RESEARCH – DEVELOPMENT- RANDOM FOREST - SCIKIT - ERPERIMENTAL- PREDICTIVE CONTROL - PYTHON - MATLAB –|
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