16 condition-monitoring-machine-learning Fellowship positions at The University of Queensland in Australia
Sort by
Refine Your Search
-
biology is highly desirable. Practical experience in bioprocess engineering, including operation of bioreactors, optimization of microbial growth conditions, and management of continuous or batch processes
-
geomechanics, or ability to quickly acquire relevant domain knowledge. Proficiency in high-performance computing (HPC) for large-scale parallel simulations. Experience with advanced constitutive models and their
-
to quickly acquire it. Familiarity with advanced statistical techniques (e.g. GAMLSS), or capacity to gain this knowledge rapidly. Proven ability to publish research, write technical reports, and communicate
-
techniques such as PCR, modular cloning, Golden Gate assembly, USER assembly, and CRISPR/Cas9-based genome editing; Sound understanding and practical experience applying the Design-Build-Test-Learn (DBTL
-
You Completion (level A and B) or near completion (level A) of a PhD in the field of Information Retrieval, Natural Language Processing, or Machine Learning on Textual Data. Demonstrated expert
-
, or soil science. Demonstrated expertise in gene expression profiling using real time PCR or high throughput sequencing. An understanding or ability to acquire knowledge of plant microbe interactions with a