PhD Candidate in Process Systems Engineering / Model Predictive Control

This is NTNU

NTNU is a broad-based university with a technical-scientific profile and a focus in professional education. The university is located in three cities with headquarters in Trondheim.

At NTNU, 9,000 employees and 43,000 students work to create knowledge for a better world.

You will find more information about working at NTNU and the application process here.

About the position

For a position as a PhD Candidate, the goal is a completed doctoral education up to an obtained doctoral degree.

The research objective of this project is to develop new Model Predictive Control algorithms for short term optimal operation of complex processes, that include contingency plans to drive the process to a safe operation regime in case of a fault.

The idea is to systematically combine methods from robust model predictive control, state estimation with online risk monitoring methods to account for fault scenarios, and to provide prioritized routes to reach a safe operation region. The contingency plans consider the current condition and state of the plant, as well as possible future degradation, maintenance and safety actions. A key aspect of this project is to systematically account for uncertainty in the models and operating conditions. A case study of hydrogen production will be used to validate the model predictive control algorithms.

The position is part of the PROSAFE MSCA doctoral training network. The recruited doctoral candidates will work as part of an international team of 12 doctoral candidates from universities and companies throughout Europe and will participate in professional and personal development training and undertake research within multidisciplinary fields of AI/ML and Process Systems Engineering for safe and efficient process operations.

Your Supervisor will be Johannes Jäschke (Johannes.jaschke@ntnu.no).

Duties of the position

• Development of robust, fault-tolerant and safety-focused model-predictive control strategies that provide contingency plans for equipment and sensor failures
• Validation of the methods in simulations on simple examples and an industrial case study for hydrogen production. Prototype software implementations
• Participation in the mobility program of the doctoral network
  • 2-3 months at DTU (Danish University of Technology, Copenhagen)
  • 2-3 months in a partner company (Kairos, Denmark)
• Supervision of master students and assistance in teaching activities subject to department needs
• Participation in NTNUs Ph.D. program, including publishing results in scientific journals and international conferences

Required selection criteria

• Professionally relevant background in one of:
  • Process Systems Engineering
  • Process Control
  • Process Safety and Maintenance with knowledge in Model Predictive Control
• Good scientific programming skills (Julia, Python, Matlab, etc)
• Some experience with nonlinear optimization methods and process modelling
• 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
• Master's students can apply, but the master's degree must be obtained and documented by the agreed starting date.
• You must meet the requirements for admission to the faculty's doctoral program
• The applicant must not have resided or carried out their main activity (work, studies, etc.) in Norway for more than 12 months in the past 3 years and be willing to spend several months at selected partner institutions.
• Good written and oral English language skills

The appointment is to be made in accordance with Regulations on terms of employment for positions such as postdoctoral fellow, Phd candidate, research assistant and specialist candidate and Regulations concerning the degrees of Philosophiae Doctor (PhD) and Philosodophiae Doctor (PhD) in artistic research national guidelines for appointment as PhD, post doctor and research assistant 

Preferred selection criteria

• Knowledge in statistical learning/machine learning, state estimation techniques
• Experience with process modelling
• Experience with methods from Reliability, Availability, Safety, Maintenance

Personal characteristics

• Curious, friendly and self-motivated
• Goal oriented and structured
• Independent and reliable
• Willing to contribute to a nice research group atmosphere

Emphasis will be placed on personal and interpersonal qualities.

Background:

PROSAFE proposes a novel doctoral training program in the multidisciplinary field combining machine learning, artificial intelligence, and process systems engineering with domain knowledge of process industry and process safety. PROSAFE will pioneer new foundations by integrating Quantitative Risk Assessment (QRA), Process Systems Engineering (PSE) with interpretable machine learning (ML), and artificial intelligence (AI) disciplines as targeted breakthroughs to achieve the objectives. To this end, PROSAFE will develop new synergistic tools and train skilled professionals to address this very important societal, economic, and environmental challenge of safe and sustainable process industries.

PROSAFE research objectives are:

1.       Harmonize robust QRA methods and implementation strategies for effective and improved risk assessment and process safety

2.       Develop AI and ML (interpretable ML) models using domain knowledge for efficient, safe, and reliable operations

3.       Develop synergistic integration of model-based with data-based methods for improved process safety operation and monitoring

4.       Demonstration and validation of PROSAFE novel concepts and methods on industrial relevant case studies for safer operation

PROSAFE’s major training objectives are:

1.       Training of DCs through individual projects combining multidisciplinary competencies in the areas of AI, ML, and PSE within the domain of process safety

2.       Establish and pilot the concept of a truly interdisciplinary European multicenter training program in AI/ML, QRA, and PSE within the domain of safety in process industries through relevant network-wide events, courses, workshops, and on-site industry training that complements training in soft skills for effective communication and entrepreneurship

Visit the project webpage (Prosafe) for more information.

We offer

• exciting and stimulating tasks in a strong international academic environment
• an open and inclusive work environment with dedicated colleagues
• favourable terms in the Norwegian Public Service Pension Fund
• employee benefits

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 Chemical Engineering within three months of employment, and that you participate in an organized PhD programme during the employment period.

The engagement is to be made in accordance with the regulations in force concerning State Employees and Civil Servants, and the acts relating to Control of the Export of Strategic Goods, Services and Technology. Candidates who by assessment of the application and attachment are seen to conflict with the criteria in the latter law will be prohibited from recruitment to NTNU. After the appointment you must assume that there may be changes in the area of work.

The position is subject to external funding.

It is a prerequisite you can be present at and accessible to the institution daily.

About the application

The application and supporting documentation to be used as the basis for the assessment must be in English.

Publications and other scientific work must be attached to the application. Please note that your application will be considered based solely on information submitted by the application deadline. You must therefore ensure that your application clearly demonstrates how your skills and experience fulfil the criteria specified above.

The application must include: 

• CV and certificates
• Cover letter
• Transcripts and diplomas for bachelor's and master's degrees. If you have not completed the master's degree, you must submit a confirmation that the master's thesis has been submitted
• A copy of the master's thesis. If you recently have submitted your master's thesis, you can attach a draft of the thesis. Documentation of a completed master's degree must be presented before taking up the position
• Project proposal
• Name and contact information of three referees
• If you have publications or other relevant research work

If all, or parts, of your education has been taken abroad, we also ask you to attach documentation of the scope and quality of your entire education, both bachelor's and master's education, in addition to other higher education. Description of the documentation required can be found here. If you already have a statement from NOKUT, please attach this as well.

We will take joint work into account. If it is difficult to identify your efforts in the joint work, you must enclose a short description of your participation.

In the evaluation of which candidate is best qualified, emphasis will be placed on education, experience and personal and interpersonal qualities. Motivation, ambitions, and potential will also count in the assessment of the candidates. 

NTNU is committed to following evaluation criteria for research quality according to The San Francisco Declaration on Research Assessment – DORA.

General information

Working at NTNU

NTNU believes that inclusion and diversity is our strength. We want to recruit people with different competencies, educational backgrounds, life experiences and perspectives to contribute to solving our social responsibilities within education and research. We will facilitate for our employees’ needs.

The city of Trondheim is a modern European city with a rich cultural scene. Trondheim is the innovation capital of Norway with a population of 200,000. The Norwegian welfare state, including healthcare, schools, kindergartens and overall equality, is probably the best of its kind in the world. Professional subsidized day-care for children is easily available. Furthermore, Trondheim offers great opportunities for education (including international schools) and possibilities to enjoy nature, culture and family life and has low crime rates and clean air quality.

As an employee at NTNU, you must at all times adhere to the changes that the development in the subject entails and the organizational changes that are adopted.

A public list of applicants with name, age, job title and municipality of residence is prepared after the application deadline. If you want to reserve yourself from entry on the public applicant list, this must be justified. Assessment will be made in accordance with current legislation. You will be notified if the reservation is not accepted.

If you have any questions about the position, please contact Professor Johannes Jäschke, email: johannes.jaschke@ntnu.no. If you have any questions about the recruitment process, please contact HR Adviser Merete Thyholdt, email: merete.thyholdt@ntnu.no.

If you think this looks interesting and in line with your qualifications, please submit your application electronically via jobbnorge.no with your CV, diplomas and certificates attached. Applications submitted elsewhere will not be considered. Upon request, you must be able to obtain certified copies of your documentation.  

Application deadline: 02.01.2025

DIVERSE INFO

Kilde: NAV stillingsannonser
https://arbeidsplassen.nav.no/stillinger/stilling/5120e826-bc74-4bc8-b2c3-3e795fd0b0a3
IMPORTAPI
https://www.jobbnorge.no/ledige-stillinger/stilling/271720