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A fully funded PhD position is available at the Norwegian University of Science and Technology in Trondheim, Norway. The position is hosted by the Department of Chemical Engineering and focuses on AI-driven spectroscopy, digital twins, and autonomous control systems for microbial bioprocesses. This opportunity is part of the AINA project and is designed to advance real-time monitoring and closed-loop control in microbial fermentation.
About NTNU
The Norwegian University of Science and Technology is a leading technical university with a strong focus on scientific research, innovation, and professional education. With a large international academic community, NTNU contributes to knowledge development for sustainable societal progress and technological advancement.
Research Focus: AI for Bioprocess Monitoring and Control
Autonomous microbial bioprocesses are currently limited by slow, off-line analytical measurements of cultivation media, which restrict real-time decision-making and adaptive control. This PhD project addresses that gap by developing artificial intelligence-enabled monitoring frameworks that convert complex sensor and spectral data into reliable state information for automated fermentation systems.
The research integrates advanced optical spectroscopy techniques, including Raman spectroscopy and complementary near-infrared (NIR) and mid-infrared (MIR) methods, with machine learning, digital twins, and uncertainty-aware AI models. Unlike purely simulation-based research, this project includes experimental validation in an automated microbial feedback control laboratory, enabling rapid iteration from algorithm development to real-world implementation.
Scope of Work
The PhD candidate will develop an end-to-end AI framework linking spectroscopy data analytics to state estimation and autonomous process control in microbial fermentation.
Core research areas include:
- Spectroscopy analytics using chemometrics, partial least squares (PLS), deep learning, calibration transfer, drift compensation, novelty detection, and uncertainty quantification
- Hybrid modeling and digital twins combining mechanistic process models with machine learning components
- State estimation and soft sensing using Kalman filter variants such as EKF and UKF, probabilistic inference, and multi-sensor data fusion
- AI-enabled closed-loop control strategies including model predictive control (MPC), adaptive control, and learning-augmented control under operational constraints
The work directly contributes to high-impact themes such as AI for scientific instrumentation, uncertainty-aware machine learning, and autonomous laboratory systems.
Key Responsibilities
The selected candidate will complete doctoral education leading to a PhD degree while conducting high-quality research within the Process Systems Engineering and Microbial Feedback Control Laboratory research groups.
Responsibilities include:
- Conducting independent research aligned with AI, spectroscopy, and bioprocess control
- Publishing scientific articles and contributing to knowledge dissemination
- Participating actively in interdisciplinary research collaboration
- Potential involvement in teaching or teaching assistance
- Adapting to evolving research and laboratory responsibilities
Required Qualifications
Applicants must hold a Master’s degree equivalent to a five-year Norwegian study program in data science, engineering cybernetics, control engineering, chemical or bioprocess engineering, biotechnology, applied mathematics, or applied physics. A strong academic background corresponding to a B average or better under NTNU’s grading scale is required.
Candidates must qualify for admission to the PhD programme in Chemical Engineering and demonstrate documented fluency in written and spoken English.
Preferred Qualifications
Advantageous qualifications include:
- Foundations in machine learning, modeling, or control systems
- Programming skills in MATLAB or Python
- Knowledge of time-series inference, spectroscopy, estimation theory, digital twins, or fermentation processes
- Laboratory experience in microbiology, fermentation, analytical chemistry, or related experimental environments
Strong quantitative candidates without prior laboratory experience will receive appropriate training.
Personal Attributes
Successful candidates should demonstrate problem-solving skills under uncertainty, especially in experimental settings where issues such as sensor drift or contamination may arise. Curiosity, structured working methods, attention to detail, and effective interdisciplinary communication are essential. A collaborative mindset and motivation to bridge AI algorithms with laboratory experimentation are highly valued.
Employment Terms and Benefits
The position is offered for a three-year period with competitive salary under the Norwegian public sector framework. Benefits include membership in the Norwegian Public Service Pension Fund, access to advanced sensing infrastructure and automated laboratories, structured supervision across AI and bioprocess domains, mentoring programs, and Norwegian language training.
Employment requires admission to the PhD programme within three months of starting and compliance with Norwegian state employment regulations, including export control legislation. Physical presence in Trondheim is required for effective academic and laboratory collaboration.
Diversity and Inclusion
NTNU values diversity, gender balance, and equal opportunity in scientific recruitment. Applicants from diverse professional and cultural backgrounds are encouraged to apply. The university promotes inclusive research environments that strengthen innovation and societal impact.
Application Requirements
Applications must be submitted electronically and include academic transcripts and diplomas, curriculum vitae, a copy of the Master’s thesis, a motivation letter explaining alignment with the project scope, relevant publications, and contact information for referees. International applicants must provide documentation verifying the scope and quality of their academic qualifications.
Living in Trondheim, Norway
The position is based in Trondheim, recognized as Norway’s technology capital with a population of approximately 200,000. The city offers a high quality of life, access to healthcare and education, subsidized childcare, international schooling options, clean air, low crime rates, and proximity to natural landscapes and cultural activities. Norway’s welfare system and research-oriented environment make Trondheim an attractive destination for doctoral studies in AI, biotechnology, and advanced process engineering.
