The School of Energy, Geoscience, Infrastructure and Society (EGIS) at Heriot-Watt 
university (HWU), Edinburgh, Scotland, has an opening for an exceptional research 
fellow position to work on the project ECO-AI (Enabling CO2 storage using 
Artificial Intelligence techniques). Further details about ECO-AI are available at 
the project webpage https://ai4netzero.github.io/eco-ai/

Purpose of Role:
The successful Research Fellow in Scientific Machine Learning is expected to 
develop model-based control and optimization techniques for multi-scale flow 
modeling of CO2 in subsurface reservoirs including the development of simplified 
complexity models for an accelerated risk assessment and optimization algorithms. 

Key Duties & Responsibilities:
-- Develop deep reinforcement learning algorithms for subsurface fluid control.
-- Develop effective fluid flow emulators using deep learning techniques.
-- Disseminate research results in peer reviewed journals and interdisciplinary 
conferences.
-- Publish open-source code repositories demonstrating all developed techniques 
and associated computational notebooks, blogs, and presentation materials.
-- Organize and lead Hackathons as a part of ECO-AI project activities. 
Participate in regular project meetings with team members and project sponsors.

How to Apply:
-- Applications can be submitted until midnight on Sunday 08th of September 2024.
https://enzj.fa.em3.oraclecloud.com/hcmUI/CandidateExperience/en/sites/CX/job/3356

Please submit via the Heriot-Watt on-line recruitment system:
(1) Cover letter describing their interest and suitability for the post;
(2) Full CV that includes the list of publications

Potential candidates who wish to discuss the post informally can contact project 
leader: Prof. Ahmed H. Elsheikh (a DOT elsheikh AT hw.ac.uk)