Senior Scientist in Multiphase Flow Modelling and Scientific Computing

IFE has a strong and internationally recognised activity in multiphase flow modelling and experimentation, with a long track record of developing technologies, software and large scale infrastructure for complex industrial transport systems.

The Department for Flow Technology combines physics based modelling, scientific computing and laboratory research, supporting applications within oil and gas production, reservoir related flow, CO₂ transport and storage, and flow assurance.

We are seeking a Senior Scientist with strong competence in multiphase flow modelling, applied fluid dynamics and scientific programming. The position will mainly focus on model development and software implementation in C++ and Python, with opportunities to contribute to experimental research in IFE’s large scale facilities, including the Well Flow Loop and FALCON. The position is offered as a three year engagement, with the possibility of transition to a permanent researcher position at IFE.

Job description

The successful candidate will contribute to ongoing and new research activities in Flow Technology, with a primary focus on modelling and software development for complex multiphase flow systems. The work will combine physics based model development, numerical implementation, analysis of experimental data and collaboration with industrial and academic partners. Key responsibilities will include:

• Develop and apply physics based multiphase flow models for industrial energy applications, with emphasis on oil and gas production, reservoir related flow phenomena, CO₂ transport and storage, and flow assurance.
• Implement, test and validate numerical models in C++ and Python as part of IFE’s modelling tools and research software.
• Use experimental data from IFE’s large scale facilities, including the Well Flow Loop and FALCON, to improve, calibrate and validate models for complex multiphase transport systems.
• Contribute to research activities related to CO₂ injection, transport and storage, including phase behaviour, pressure drop, transient flow, operational limits and flow stability.
• Apply modern computational methods, including data processing, uncertainty assessment, automated workflows, machine learning and hybrid physics based and data driven modelling.
• Design, analyze and interpret laboratory experiments when relevant, in collaboration with experimental researchers and technical personnel.
• Contribute to research proposals, scientific publications, technical reports and collaboration with industrial and academic partners.

Qualification requirements

Applicants should meet the following requirements:

• PhD orequivalent doctoral degree in a field relevant to the position, such as applied mathematics, physics, mechanical engineering, chemical engineering, petroleum engineering, reservoir engineering, computational science or a related discipline.
• Strong knowledge of multiphase flow, fluid dynamics, transport phenomena or reservoir related flow processes.
• Experience with numerical modelling, scientific computing and implementation of physical models.
• Strong programming skills, preferably in C++ and Python.
• Experience with model validation, uncertainty assessment, data analysis or processing of experimental data.
• Interest in applying modern computational methods, including machine learning, AI assisted modelling or hybrid physics based and data driven approaches.
• Good ability to work independently as well as in multidisciplinary teams involving researchers, software developers, experimentalists and industrial partners.
• Excellent oral and written communication skills in English.

Personal qualifications

Applicants should meet the following requirements:

• PhD or equivalent doctoral degree in applied mathematics, physics, mechanical engineering, chemical engineering, petroleum engineering, reservoir engineering, computational science or a related discipline.
• Strong competence in multiphase flow, fluid dynamics, transport phenomena or reservoir related flow processes.
• Experience with numerical modelling, scientific computing and implementation of physical models.
• Strong programming skills in C++ and Python, or documented ability to develop high quality scientific software in comparable languages.
• Experience with model validation, uncertainty assessment, data analysis or processing of experimental data.
• Interest in modern computational methods, including machine learning, AI assisted modelling, automated workflows or hybrid physics based and data driven approaches.
• Excellent oral and written communication skills in English.

It is an advantage if the candidate has experience with:

• CO₂ transport, CO₂ injection, CCS, reservoir simulation or flow assurance.
• Industrial research projects or collaboration with industry partners.
• Laboratory experiments, high pressure flow systems or experimental data analysis.
• Scientific publications, proposal writing or supervision of students.

We offer

IFE offers competitive salary, pension and insurance schemes, but above all we offer an opportunity forpersonal development that few others can offer. The position entails a opportunity to influence yourdevelopment to become part of a larger community of specialists. You will be working in aninterdisciplinary, international environment. You will be part of a stimulating work environment withskillful, experienced, and creative colleagues. Be able to come in contact with well-established nationaland international scientific and industrial networks.

IFE is subject to the Security Act, which includes requirements for the organisation’s management of critical national information, as well as other relevant legislation concerning the management of sensitive information. On this basis, it is a prerequisite for employment that the applicant is suitable from a security perspective. Note that relevant applicants will be asked questions that are necessary to ascertain this. This includes questions about any ties to countries that the PST has classified as a ‘high-risk country’ in its open threat assessment. Background checks are performed as part of our recruitment process.

We view diversity as a strength in our work. We therefore encourage all qualified candidates to apply regardless of age, gender, disability, sexual orientation, religion and ethnic background. We place great emphasis on your personal suitability for the position.