M-2124 Phd Student in Data-driven Modelling and

Description
**Are you passionate about research? So are we Come and join us**:
The Luxembourg Institute of Science and Technology (LIST) is a Research and Technology Organization (RTO) active in the fields of materials, environment and IT. By transforming scientific knowledge into technologies, smart data and tools, LIST empowers citizens in their choices, public authorities in their decisions and businesses in their strategies.

**You ‘d like to contribute as a researcher? Join our Materials Research and Technology department**:
Through its research into advanced materials and processes, the “Materials Research and Technology” (MRT) department, with its 200 researchers and engineers, contributes to the emergence of enabling technologies that underpin the innovation processes of local and international industry. MRT’s activities hinge on four thematic pillars: nanomaterials and nanotechnology, scientific instrumentation and process technology, structural composites, and functional polymers.

The department also includes four high-tech platforms, focusing on composites, prototyping, characterization and testing. These platforms serve both LIST research staff, and other stakeholders in Luxembourg.

**Responsibilities**:
**How will you contribute?**:
You will be joining HYMAT that is a large and multidisciplinary project that focuses on the discovery and development of materials for hydrogen generation and utilization. HYMAT is built around 8 highly complementary research axes, which will address key materials challenges faced in establishing specific technologies that will underpin the hydrogen economy.

The PhD student will work in the framework of the HYMAT research axis #1: Machine Learning for PEC Cell Design & Optimization. A detailed understanding of PEC cell processes (e.g. between photo-absorbers, electrolytes, and catalysts) is essential to achieving efficiencies approaching the theoretical maximum. A fundamental understanding of how molecular-level (e.g. of reaction pathways), and material composition influence performance (e.g. structure-activity relationships) is required. This should include physical phenomena (e.g. electrolyte flow rate, charge carrier transport, reaction kinetics and thermodynamics).

The proposed research aims at combining and integrating physical-based and data-driven modelling and simulation and optimization to enable material screening, cell configuration and operational optimization (e.g. for efficiency).

Must Have Requirements
- You hold a master’s degree in Computational Engineering, Material Science or related topics
- Excellent knowledge of computational methods
- Proven hands-on experience with machine learning
- Good knowledge in programming
- Fluency in English is a must

We offer
**Your LIST benefits**:
An organisation with a passion for impact and strong RDI partnerships in Luxembourg and Europe that works on responsible and independent research projects;
Sustainable by design, empowering our belief that we play an essential role in paving the way to a green society;
Innovative infrastructures and exceptional labs occupying more than 5,000 square metres, including innovations such as our Viswall, high-scale incubators and top of the range 3D/4D printings that are part of our toolkit for excelling in all we do;
Multicultural and international work environment with more than 45 nationalities represented in our workforce;
Diverse and inclusive work environment empowering our people to fulfil their personal and professional ambitions;
Gender-friendly environment with multiple actions to attract, develop and retain women in science;
32 days paid annual leave, 11 public holidays, flexible working hours, 13-month salary, statutory health insurance and access to lunch vouchers;
Personalised learning programme to foster our staff’s soft and technical skills;
An environment encouraging curiosity, innovation and entrepreneurship in all areas.

A motivation letter oriented towards the position and detailing your experience;
A scientific CV with contact details;
List of publications (and patents, if applicable);
Contact details of 2 references.

**Application procedure and conditions**:

- Applications will be reviewed on an ongoing basis until the position is filled;
- The main criteria for selection will be the correspondence of the existing skills and expertise of the applicant with the requirements mentioned above.

**PhD additional conditions**:

- Supervisors at LIST: Dr Salim Belouettar, Dr. Ahmed Makradi & Dr. N. Boscher
- Work location: Luxembourg Institute of Science and Technology (LIST), Belvaux, Luxembourg
- PhD enrolment: University of Luxembourg, Belval, Luxembourg
- Please note the universities costs are at the charge of the student.

Languages English Education Master Experience 1+ years