PhD scholarship in Data Science Applications using Multi-Scale Models for Sustainable Bioproduction - DTU Biosustain


BEMÆRK: Ansøgningsfristen er overskredet

Are you interested in pioneering advancements in AI technology and its practical implementation in the realm of sustainable development? If you are motivated to guide innovation by predicting real world impact of bio-based products using data science applications and you are looking for an opportunity to contribute to a sustainable transition, you have it right here.

While a sustainable bio-based industry is technically feasible, significant challenges persist. Establishing a data science-based workflow is crucial for identifying and enhancing key features in fermentation technology to boost sustainability. Economic competitiveness and the environmental impact of bio-based products must be assessed, and the generated information must be used to guide fundamental developmental activities at various Technology Readiness Levels (TRLs). Access to a framework that integrates these aspects is vital for advancing systems metabolic engineering. We have a PhD student opening at DTU Biosustain, focusing on integrating AI technology and data-driven models across metabolism, bioprocess, and the economy to develop a robust data science infrastructure for improving the sustainability footprint of bioprocess.

DTU Biosustain, in collaboration with the DTU Bioengineering, is offering a PhD position to foster next generation of hybrid scientists by blending expertise in machine learning, deep-learning, constraint based modeling and quantitative sustainability assessments. The goal of this PhD is to develop data science-based methods and framework predict sustainability performance of bio-based products at early TRLs. The tools developed by the PhD student will guide fundamental research in biotechnology.

You will become a member of the Sustainable Innovation Office at DTU Biosustain under the supervision of Senior Researcher Sumesh Sukumara (as a Main Supervisor). Additionally, you will be interacting with the Bio Digitalization and Data team under the supervision of Assistant Professor Marjan Mansourvar (as a Co-Supervisor) from DTU Bioengineering.

Responsibilities and qualifications
You'll develop framework and workflows to apply the latest algorithms and data science methods related to synthetic biotechnology and sustainability. The Ph.D. candidate will work on a project focusing on sustainability, economics, and computational science. Specifically, the candidate will be involved in cutting-edge research and contribute to the development of collective intelligence theories and methodologies.

Your primary research tasks will be to:

  • Engage in interdisciplinary research to connect data science with sustainability assessment tools.
  • You will do so by bridging various open-source libraries to exchange information with each other and eventually use it to predict sustainability performance.
  • Developing and enacting protocols for data collection.
  • Simulate a multi-scale, multi-sector framework with features generated during the fundamental scientific experiments.
  • Utilizing advanced statistical and computational methods to analyze and interpret research findings.
  • Bioprocess Development: Contribute to bioprocess development across scales in a new data-driven paradigm.
  • Machine Learning Expertise: Develop and apply state-of-the-art machine learning and deep learning techniques to biotechnological problems.
  • Discover the responsibilities of a researcher and the specific steps involved in doing research.
  • Publishing research outcomes in high-impact journals and presenting findings at conferences and seminars.

Your ideas and inputs e.g., new methods, tools and analysis are highly welcomed.

You must have a two-year master's degree (120 ECTS points) or a similar degree with an academic level equivalent to a two-year master's degree.

  • MSc degree in relevant field, such as data science, biotechnology, or chemical/process engineering. Applicants with a hybrid background are highly desired.
  • Process knowledge of research methodologies, experimental design, and data analysis techniques. 
  • Background in data science, machine learning, deep learning, and/or bioinformatics including programming and mathematical modelling. Showcase a robust research background in computational modeling and/or data science.
  • Advanced proficiency in software development and data management (with Python, R, or other programming languages such as MATLAB or C++.).
  • Proven experience in working with large sets of public or proprietary databases.
  • Engagements in solving sustainability and biotechnology challenges with courses or external projects.
  • Ability to translate domain-specific problems into data science and engineering solutions.
  • Excellent communication and interpersonal skills for working in a multi-disciplinary team environment.
  • Demonstrate outstanding communication and interpersonal abilities and the capacity to collaborate effectively within interdisciplinary teams.

If you have these competencies and experience listed above, and you have initiative, are motivated, and are eager to learn more and further improve, then you are good to go.

Approval and Enrolment  
The scholarship for the PhD degree is subject to academic approval, and the candidate will be enrolled in one of the general degree programmes at DTU. For information about our enrolment requirements and the general planning of the PhD study programme, please see DTU's rules for the PhD education

We offer
DTU is a leading technical university globally recognized for the excellence of its research, education, innovation and scientific advice. We offer a rewarding and challenging job in an international environment. We strive for academic excellence in an environment characterized by collegial respect and academic freedom tempered by responsibility.

Your New Team - Sustainable Innovation Office
At the Novo Nordisk Foundation Center for Biosustainability (DTU Biosustain), you will work in the Sustainable Innovation Office. Our focus is to guide innovation at an early stage by assessing the benefits (society, economic and environmental) of developed bio-based technologies. We aim to develop computational tools that provides insights to guide the research community in DTU and beyond to assess the sustainability of bio-based products. Our work environment is informal and characterised by knowledge sharing, respect, trust, and room for having an enjoyable time together – naturally balanced with creating tangible results. Now, we are just looking forward to welcoming you to the team.

Salary and appointment terms 
The appointment will be based on the collective agreement with the Danish Confederation of Professional Associations. The allowance will be agreed upon with the relevant union. The period of employment is 3 years.

You can read more about career paths at DTU here .

Further information  
If you need additional information about the position, please contact Sumesh Sukumara at and Marjan Mansourvar at  

You can read more about the involved departments at:

DTU Biosustain 

DTU Bioengineering  

If you are applying from abroad, you may find useful information on working in Denmark and at DTU at DTU – Moving to Denmark . Furthermore, you have the option of joining our monthly free seminar “PhD relocation to Denmark and startup “Zoom” seminar ” for all questions regarding the practical matters of moving to Denmark and working as a PhD at DTU. 

Application procedure 
Your complete online application must be submitted no later than 15 March 2024 (23:59 Danish time).

Applications must be submitted as one PDF file containing all materials to be given consideration. To apply, please open the link "Apply now", fill out the online application form, and attach all your materials in English in one PDF file . The file must include:

  • A letter motivating the application (cover letter)
  • Curriculum vitae 
  • Grade transcripts and BSc/MSc diploma (in English) including official description of grading scale
  • List of publications

You may apply prior to ob­tai­ning your master's degree but cannot begin before having received it. 

Applications received after the deadline will not be considered.

All interested candidates irrespective of age, gender, race, disability, religion or ethnic background are encouraged to apply.

DTU Biosustain is an internationally oriented institution of higher learning committed to an educational system based on the highest standards of teaching and research. We focus on developing methods for large-scale production of sustainable foods, sustainable bio-chemicals, and natural products, alongside breakthroughs in automation, analytics, and data science. At the center, big data approaches and the analysis of biological systems serve as pivotal research tools. DTU Biosustain applies these innovations to design microbial cell factories, aiming to promote sustainable practices in three key application areas: Sustainable Chemicals, Natural Products, and Microbial Foods. Discover more at

Technology for people
DTU develops technology for people. With our international elite research and study programmes, we are helping to create a better world and to solve the global challenges formulated in the UN’s 17 Sustainable Development Goals. Hans Christian Ørsted founded DTU in 1829 with a clear mission to develop and create value using science and engineering to benefit society. That mission lives on today. DTU has 13,500 students and 6,000 employees. We work in an international atmosphere and have an inclusive, evolving, and informal working environment. DTU has campuses in all parts of Denmark and in Greenland, and we collaborate with the best universities around the world.


- Arbejdspladsen ligger i:

Lyngby-Taarbæk Kommune

-Virksomheden tilbyder:


Danmarks Tekniske Universitet, Anker Engelunds Vej, 2800 Kongens Lyngby


Ansøgningsfrist: 15-03-2024; - ansøgningsfristen er overskredet

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Denne artikel er skrevet af Emilie Bjergegaard og data er automatisk hentet fra eksterne kilder, herunder JobNet.
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