PhD Candidate in Hybrid Machine Learning
6 months ago
About the job
For a position as a PhD Candidate, the goal is a completed doctoral education up to an obtained doctoral degree.
This PhD opportunity offers a unique chance to be at the forefront of the transformative field of hybrid modelling, combining the power of machine learning with physics-based approaches. Unexpected high overpressures in the subsurface continue to challenge oil and gas exploration on the Norwegian Continental Shelf, posing risks such as mud loss, kicks, and well loss. This PhD will focus on developing innovative solutions by integrating 3D pressure stochastic simulations with advanced machine learning techniques to enhance pore pressure prediction workflows. By improving the accuracy and robustness of subsurface pressure predictions, this research aims to make drilling operations safer and more cost-effective. As part of the research project “Hybrid Modelling with Machine Learning for Overpressure and Mud Weight Prediction – Big Pressure”, you will contribute to cutting-edge advancements that merge physical science and artificial intelligence.
Your immediate leader is Professor Adil Rasheed.
Duties of the position
• Set up research plans with the help of the supervisor team and conduct them accordingly.
• Take lead in research idea generation and research paper writing
• Establish close cooperation with other researchers within the project
• Comply with the PhD training programme of the faculty
Required selection criteria
You must have a professionally relevant background in mathematics and/or cybernetics, computer science, physics, geology. Your education must correspond to a five-year Norwegian degree program, where 120 credits are obtained at master's level You must have a strong academic background from your previous studies and an average grade from the master's degree program, or equivalent education, which is equal to B or better compared with NTNU's grading scale. If you do not have letter grades from previous studies, you must have an equally good academic basis. If you have a weaker grade background, you may be assessed if you can document that you are particularly suitable for a PhD education. You must meet the requirements for admission to the .The appointment is to be made in accordance with and
Preferred selection criteria
• Machine Learning Experience: Previous experience and practical skills in machine learning.
• Mathematical Proficiency: Knowledge of partial differential equations and numerical methods.
• Programming Skills: Proficiency in Python programming; experience with C++ is a plus.
• Communication Skills: Strong written and oral English communication abilities.
Personal characteristics
Ability to work independently as well as in cross-disciplinary teams. Ability to interact and collaborate with actors in academia, public sector, and industry. Ability to thrive and contribute to the work environment. Be self-motivated, focused, and goal-oriented, be committed and keep deadlines, be flexible, reliable, and solution-orientated, be innovation-driven, enthusiastic, and ambitious. Be scientifically curious and open to new research challenges, demonstrate persistence in addressing technical problems. Good communication and dissemination skills.
We offer
exciting and stimulating tasks in a strong international academic environment an open and with dedicated colleagues favourable terms in the
Salary and conditions
As a PhD candidate (code 1017) you are normally paid from gross NOK 532 200 per annum before tax, depending on qualifications and seniority. From the salary, 2% is deducted as a contribution to the Norwegian Public Service Pension Fund.
The period of employment is 3 years.
Appointment to a PhD position requires that you are admitted to the PhD programme in within three months of employment, and that you participate in an organized PhD programme during the employment period.
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