368 data "https:" "https:" "https:" "https:" "Dr" "UCL" positions at Monash University
Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Field
-
back at least as far as 1954 (Dowe, 2008a, sec. 1, pp549-550). Discussion of how to do this using the Bayesian information-theoretic minimum message length (MML) approach (Wallace and Boulton, 1968
-
techniques in bacterial genomics, including both short- (Illumina) and long-read sequencing (Oxford Nanopore), data mining of electronic medical records and use of machine learning to predict several outcomes
-
Advisory System, or data from other implantable or wearable devices. This involves consideration of both feature-based machine learning or data science approaches and neural mass parameter estimation
-
-disciplinary team of clinician scientists and computer scientists to develop diagnosis/predictive/treatment/robotics surgery models of diseases of interest using multimodal medical data, consisting of images
-
-employment and/or background checks required for the role, as determined by the University. Enquiries: Dr Thomas Tapmeier, Head, Uterine Biology & Gynaecological Disease Group, +61 3 8572 2386 Position
-
of the U.S. workforce. We then consider various attributes of these occupations, as given by the Occupational Information Network (O*NET) data-base. Using a subset of these occupations, we survey a
-
extract events and mine knowledge from existing unstructured/structured data, and exploit the knowledge via neuro-symbolic reasoning for crime prevention (eg -sexual assaults), especially when there is no
-
nutritional data into a user-friendly platform, enabling consumers, restaurants, and policymakers to make informed food choices and reduce diet-related emissions. Required knowledge Data analytics and software
-
on clinical, genomics and functional dependency data (CRISPR, drug screens). Brain tumours represent the second most common cancer and the most common solid tumour in childhood in general. Paediatric brain
-
motif, hence renders the identification of the binding protein difficult. Here we propose for the first time to apply the Bayesian information-theoretic Minimum Message Length (MML) principle to optimise