19 coding-"https:"-"Prof"-"FEMTO-ST" "https:" "https:" "https:" "https:" "https:" "Dr" "https:" Fellowship research jobs at The University of Queensland
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in human induced pluripotent stem cells (hiPSCs)-derived skin organoids (https://pubmed.ncbi.nlm.nih.gov/38044307/ ), and the generation of vascularized skin organoids (https
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analytics More information can be found at https://smi.uq.edu.au/mishc About This Opportunity This is an exciting opportunity for a Professorial Research Fellow to work within the Minerals Industry Safety and
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opportunities for student supervision and career development. For more about the Fairlie Group please visit - https://imb.uq.edu.au/research-groups/fairlie . Key responsibilities will include: Research
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of foresight in young children. Working with project leads Professor Thomas Suddendorf, Dr Kristy Armitage and Dr Sarah Coundouris, you will have the opportunity to develop your expertise and emerging research
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or Research Fellow to contribute to groundbreaking quantum algorithms research led by Dr Riddhi Gupta and Associate Professor Sally Shrapnel. You’ll work at the forefront of theory, simulation and
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funding Knowledge on a coding language (Phyton, etc) The successful candidate may be required to complete a number of pre-employment checks, including: right to work in Australia, conduct concerning gender
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(e.g., LabArchives, BioRender). Desirable Demonstrated experience in fermentation control, optimisation and scale-up. Experience in the use of electronic lab books Experience in coding languages (Python
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contact Dr Joel Carpenter j.carpenter@uq.edu.au . For application inquiries, please reach out to the Talent Acquisition team at talent@uq.edu.au, stating the job reference number (below) in the subject line
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opportunity, please contact Dr Yosephine Gumulya, y.gumulya@uq.edu.au or Dr Huadong Peng, huadong.peng@uq.edu.au. For application inquiries, please reach out to the Talent Acquisition team at talent@uq.edu.au
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results. High levels of personal integrity, transparency and capability. Experience in crop model coding is desirable. Experience in statistical analysis and data visualisation (e.g. R, Python) is desirable