It is planned to develop reduced models for various water treatment processes, characterized by **complex multiphase flows** that may include biological and/or chemical reactions. However, the aim is that the **methodologies developed **for model reduction **can be applied in any other field of engineering** where the flow of one or several fluids plays a predominant role.
- Multiphase flow simulation.
- Turbulence modeling.
- Use of different types of neural networks for solving engineering problems.
Training activities for scientific, professional and personal development.
**Working schedule**:
- 7.75 hours per day.
- Versátil timetable: start between 8:00 and 9:30. Fridays with the possibility of a continuous working day.
- Summer timetable: Only mornings starting June 15th and finishing August 31st (5.5 hours).
**Holidays**:
- 23 working days + Christmas holidays (24-Dec to 2-Jan).
**Degree**: Master's Degree in: Industrial Engineering, Mechanical Engineering or Chemical Engineering.
**Languages**: English
**IT knowledge**:
- Computational Fluid Dynamics (CFD) simulation tools.
- Phyton.
- TensorFlow, Pytorch, Keras.
**Others**:
- Solid knowledge of Fluid Mechanics.
- Knowledge in Machine Learning and Deep Learning tools.
- Ability to work in a multidisciplinary team
***Starting date**:Early 2025