Sort by
Refine Your Search
-
Listed
-
Country
-
Employer
-
Field
-
in a PhD thesis submitted to the University of Oslo. We seek a highly motivated candidate with a strong background in molecular biology, human genetics/genomics, data mining, machine learning, and
-
and ambitious researcher with a strong background in molecular biology, human genetics/genomics, bioinformatics, machine learning, data mining, and computational programming, including software
-
in a PhD thesis submitted to the University of Oslo. We seek a highly motivated candidate with a strong background in molecular biology, human genetics/genomics, data mining, machine learning, and
-
be preferred. Requirements: PhD degree in Learning Sciences, Educational Technology, Human-Computer Interaction (HCI), Information Technology, AI, or a relevant field Demonstrated experience and
-
and ambitious researcher with a strong background in molecular biology, human genetics/genomics, bioinformatics, machine learning, data mining, and computational programming, including software
-
. Further information can be found by viewing UQ’s Criteria for Academic Performance . About You To be successful in this opportunity, you will bring: Completion of a PhD in a relevant discipline such as
-
- $113,659.72 + 17% super (Academic Level A) Based at our St Lucia Campus with occasional travel to mine sites About This Opportunity Join The University of Queensland as a Postdoctoral Research Fellow and
-
environment where your work contributes to shaping sustainable mining practices globally. As part of the Centre for Environmental Responsibility in Mining (CERM), you will work alongside an interdisciplinary
-
computational methods expertise, including Python, R or similar languages, machine learning, NLP, text mining and reproducible coding practices. Experience analysing social media data using qualitative
-
computational methods expertise, including Python, R or similar languages, machine learning, NLP, text mining and reproducible coding practices. Experience analysing social media data using qualitative