PhD Position in Digital Twin-enabled Validation and Maintenance for Pharma Industrial Processes, Denmark

  •  PhD
  •  31-Aug-2025
  •   Denmark
  • $$  Varies

Aarhus University’s Graduate School of Technical Sciences, in collaboration with Technicon, invites applications for an Industrial PhD position on Digital Twin-enabled Validation and Maintenance for Pharma Industrial Processes. The project aims to advance digital twin technologies to optimize product validation, reduce time-to-market, and enhance maintenance processes in the pharmaceutical industry.

To be eligible for this PhD position, applicants must hold a relevant master’s degree in computer engineering, computer science, robotics, or a related field. They should have a strong background in digital twin engineering, autonomous systems, and machine learning, along with skills in cyber-physical modelling, autonomous agents, probability and statistics, and programming with Python or R. Previous experience in developing models, tools, or processes is considered an advantage.

Founded in 1928, Aarhus University is one of Denmark’s leading research-intensive institutions and consistently ranked among the world’s top universities. Located in the vibrant city of Aarhus, it offers a wide range of academic programs across science, engineering, health, arts, and business. The university is known for its strong focus on interdisciplinary research, innovation, and collaboration with industry, making it an attractive destination for international students and researchers seeking high-quality education and cutting-edge research opportunities.

Aarhus Universitet Information

Aarhus Universitet Grants

PhD Position in Digital Twin-enabled Validation and Maintenance for Pharma Industrial Processes, Denmark Established in 1928, Aarhus Universitet (Aarhus University) is a non-profit public higher education institution located in the urban setting of the small city of Aarhus (population range of 250,000-499,999 inhabitants), Central Denmark Region. Officially accredited and/or recognized by the Uddannelses- og Forskningsministeriet (Ministry of Higher Education and Science, Denmark), Aarhus Universitet (AU) is a very large (uniRank enrollment range: 35,000-39,999 students) coeducational higher education institution. Aarhus Universitet (AU) offers courses and programs leading to officially recognized higher education degrees in several areas of study. See the uniRank degree levels and areas of study matrix below for further details. This 91 years old higher-education institution has a selective admission policy based on students' past academic record and grades. International applicants are eligible to apply for enrollment.

Eligibility Criteria

  • Eligible Countries: Applicants from all countries are welcome.

  • Acceptable Course or Subjects: The scholarship will be awarded for PhD research in Electrical and Computer Engineering or related fields.

  • Admissible Criteria: To be eligible, applicants must:

    • Hold a relevant Master’s degree in computer engineering, computer science, robotics, or similar fields.

    • Have a background in digital twin engineering, autonomous systems, and machine learning.

    • Possess expertise in cyber-physical modelling, digital twins, autonomous agents, multi-agent systems, probability & statistics (including Python/R).

    • Preferably have prior experience in developing models, tools, or processes.

Offered Benefits

  • Industrial PhD employment with equal time split between Aarhus University and Technicon.

  • Collaboration with a highly skilled interdisciplinary team.

  • Flexible working conditions and a supportive research environment.

  • Opportunity to work on state-of-the-art digital twin technology with strong industrial applications.

  • Full funding (subject to Innovation Fund Denmark approval).

Application Process

  • Submit your application online via the official Aarhus University portal (link provided in the call).

  • Include the required project description (can be copied from the announcement), CV, transcripts, and other mandatory attachments as per the application guide.

  • Preferred Start Date: 1 January 2026 (flexible)

For further information, contact:

  • Peter G. Larsen (Main Supervisor):

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