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"Bioprocess Engineer"

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Bioprocess Engineer

Job Description:

About This Opportunity

We are seeking a multi-disciplinary Bioprocess Engineer with strong foundations in chemical or bioprocess engineering and hands-on experience in computational modelling. You will lead the development of the bioprocess physics layer of the digital twin and support the machine-learning infrastructure that integrates CFD outputs with biological datasets.

This role bridges engineering, computational modelling, and experimental integration — ideal for someone comfortable working across simulation, coding, and data-driven modelling.

Key responsibilities will include:

Research:

  • Interpret CFD models of pilot and lab-scale bioreactors (e.g. mixing time, kLa, flow fields).
  • Analyse reactor geometry, operational ranges, and hydrodynamic KPIs across scales.
  • Develop the scale-down mapping framework and support design of reactor control strategies.
  • Build the codebase for integrating CFD, experimental data, and physics-informed ML models (e.g., PINNs).
  • Develop and validate the bioprocess layer of the digital twin.
  • Assist in training and validating the biological layer using fermentation data.
  • Support real-time integration of models into Python-based reactor control systems.
  • Prepare engineering reports, documentation, and milestone deliverables.
  • Report regularly with the industrial partner.
  • Other duties, as reasonable directed by the supervisor
  • Produce quality research outputs consistent with discipline norms by publishing or exhibiting in high quality outlets.
  • Review and draw upon best practice research methodologies.

Supervision and Researcher Development:

Supervise Honours and Higher Degree by Research students, supervise and manage employees, provide performance feedback and training, resolve conflicts, and ensure correct remuneration and benefits.

Citizenship and Service:

Develop partnerships, demonstrate leadership through mentoring, engage in internal service roles and committees, perform administrative functions, provide support to colleagues, and uphold university values.

This is a research focused position. Further information can be found by viewing UQ’s Criteria for Academic Performance.

About You

You are an experienced and highly motivated researcher to apply their subject matter expertise to create a Digital Twin infrastructure within the Food and Beverage Accelerator.

You will have:

  • Undergraduate and PhD degrees in Chemical Engineering, Bioprocess Engineering, Mechanical Engineering, or related field.
  • A working knowledge of how to interpret CFD model outputs.
  • Strong programming ability in Python (including scientific libraries)
  • Understanding of mixing, mass transfer, reactor design, and bioprocess hydrodynamics.
  • Ability to translate computational outputs into practical experimental guidance.
  • Experience with machine learning or interest in physics-informed ML approaches
  • Strong problem-solving skills with the ability to plan, prioritize tasks, meet deadlines, and work adaptably both independently and in a team.
  • Strong interpersonal and communication skills with proven ability to produce clear, succinct documentation.

Desirable

  • Experience with physics-informed neural networks (PINNs) or hybrid ML/physics modelling.
  • Experience with generating CFD models of bioreactors.
  • Experience interacting with hardware via APIs or control systems.
  • Familiarity with microbial bioprocessing and fermentation data.
  • Experience with DevOps or structured codebase management (Git, Docker).

The successful candidate may be required to complete a number of pre-employment checks, including: right to work in Australia, conduct concerning gender-based violence etc.

You must maintain unrestricted work rights in Australia for the duration of this appointment to apply. Employer sponsored work rights are not available for this appointment.

Want to Apply?

We welcome applications from all individuals and are committed to an inclusive and accessible recruitment process. To be considered, please ensure you upload:

  • Resume
  • Cover letter
  • Responses to the ‘About You’ section

Job reference: R-59580

Applications close Sunday, 4 January 2026 at 11.00pm AEST (R-59580).

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