PhD Position in AI-assisted multi-scale modelling Protonic Ceramic Electrolysers

10 Jan 2024
Job Information

Organisation/Company

University of Twente (UT)

Research Field

Physics

Researcher Profile

First Stage Researcher (R1)

Country

Netherlands

Application Deadline

11 Feb 2024 - 22:59 (UTC)

Type of Contract

Temporary

Job Status

Not Applicable

Hours Per Week

40.0

Is the job funded through the EU Research Framework Programme?

Not funded by an EU programme

Is the Job related to staff position within a Research Infrastructure?

No

Offer Description

Power-to-methane (PtM) using CO2 as feedstock is a highly attractive prospect as it allows the storage and distribution of intermittent renewable energy via the existing gas grid infrastructure with the added benefit of direct CO2 utilisation. Conventional PtM concepts involve integration of a water/steam electrolysis unit for H2 production with a CO2 methanation unit. However, proton-conducting ceramic electrolysers offer the unique opportunity to combine both processes into a single unit thereby decreasing plant complexity and improving overall process efficiency.

In this Dutch-German bilateral project, in collaboration with our German partners EIFER, WZR Ceramics and Forschungzentrum Jülich as well as Dutch partner Shell, you will investigate the feasibility and scale-up of such an integrated concept. Your principal task will be the development of a multiscale multiphysics model of the protonic electrolyser system for e-methane production from CO2 and steam. You will adapt the AI-assisted cell-to-stack-to-system multiscale model framework developed in our lab to do this. The framework attempts to capture and couple the relevant physics at all involved scales. The goal of your work will be to provide guidelines for cell and stack design (including the effect of statistical cell-to-cell manufacturing variations on stack performance and reliability), balance-of-plant design and system operating conditions that maximise overall system efficiency and minimize levelized cost of fuel production.

Requirements
Specific Requirements

• You have a Master’s degree in chemical engineering, mechanical engineering, physical chemistry or a related field.
• You have experience and/or strong interest in numerical modelling and machine learning.
• You have experience and/or strong interest in coding, particularly in C++.
• You are an excellent team player in an enthusiastic group of scientists and engineers working on a common theme.
• You are creative, like to push boundaries, and are highly motivated to address a major challenge for the low carbon energy and chemicals transition.
• You are fluent in English and able to collaborate intensively with external parties in regular meetings and work visits.

Additional Information
Benefits

• You will be appointed on a fulltime position for 4 years.
• The university offers a dynamic ecosystem with enthusiastic colleagues in a stimulating scientific environment.
• The gross monthly PhD salary is € 2,770.- in the first year and increases to € 3,539.- in the fourth year.
• The offer further includes excellent benefits such as a holiday allowance of 8% of the gross annual salary and a year-end bonus of 8.3%, a solid pension scheme, a minimum of 29-day holidays, and numerous professional and personal development programs.
• Free access to sports facilities on campus.
• You will have a training programme as part of the Twente Graduate School where you and your supervisors will determine a plan for a suitable education and supervision.

Additional comments

Your application should include a cover letter, emphasizing your specific interest and motivation, a detailed CV including the name and e-mail address for at least two references, and an academic transcript of B.Sc. and M.Sc. education. An interview and a scientific presentation will be part of the selection procedure.

For more information about the position, you are welcome to contact Dr.-Ing. Aayan Banerjee ([email protected] ).

Please apply via the button below.

Website for additional job details

https://www.academictransfer.com/336467/

Work Location(s)

Number of offers available

1

Company/Institute

Universiteit Twente

Country

Netherlands

City

Enschede

Postal Code

7522NB

Street

Drienerlolaan 5

Geofield

Where to apply

Website

https://www.academictransfer.com/en/336467/phd-position-in-ai-assisted-multi-sc…

Contact

City

Enschede

Website

http://www.universiteittwente.nl/

Street

Drienerlolaan 5

Postal Code

7522 NB

STATUS: EXPIRED