162 molecular-dynamics-simulations positions at Monash University in Australia

MPCCC Project Coordinator (Molecular Tumour Board)

MPCCC Project Coordinator (Molecular Tumour Board) Job No.: 665100 Location: Clayton campus Employment Type: Part-time, fraction (0.8) Duration: Fixed-term appointment until 25 May 2025 Remuneration

Research Fellow (Immunity) - Biochemistry & Molecular Biology

Research Fellow (Immunity) - Biochemistry & Molecular Biology Job No.: 664036 Location: Clayton campus Employment Type: Full-time Duration: 12-month fixed-term appointment Remuneration: $78,120

Lecturer (Simulation) - Victorian Heart Institute

Lecturer (Simulation) - Victorian Heart Institute Job No.: 663959 Location: Victorian Heart Hospital Employment Type: Part-time, fraction (0.4) Duration: Continuing appointment Remuneration: Pro

Simulating Collaborative Discourse

this issue, we propose to develop methods for simulating collaborative discourse data. Preliminary work by Swiecki and colleagues (in preparation) has shown that it is possible to accurately simulate

Anomaly detection in evolving (dynamic) graphs

to devise adaptive models that take into account the dynamically changing characteristics of environments and detect anomalies in ‘evolving’ data. Over the last two decades, many algorithms have been proposed

Creating a turnkey solution to classify, predict and simulate behaviour from videos of rodents

. Methods To make this pre-trained model, the student will script a virtual mouse model 13 to traverse through common behavioural apparatuses within a realistic simulation tool called Unreal Engine 14

Clustering of (time series of) generalised dynamic Bayesian nets, etc.

-9. [Final camera ready copy was submitted in October 2003.] D. L. Dowe (2008a), "Foreword re C. S. Wallace ", Computer Journal , Vol. 51, No. 5 (Sept. 2008) [Christopher Stewart WALLACE (1933-2004

Unlocking time: machine learning for understanding dynamic processes

The world is dynamic and in a constant state of flux, yet most machine learning models learn static models from a dataset that represents a single snapshot in time. My group's research is

Learning in a dynamic and ever changing world

The world is dynamic, in constant flux. However, machine learning typically learns static models from historical data. As the world changes, these models decline in performance, sometimes

Research Fellow - Brain Rehabilitation and Recovery Research Group

, overseeing research procedures, and analysing data. Engaging in preclinical work utilizing rodent trauma models, neuropharmacology, neuroimaging (e.g., MRI), and cellular and molecular methods. Participating