241 communications-"https:"-"https:"-"https:"-"https:"-"https:" positions at Monash University
Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Field
-
Media and Communications Adviser Job No.: 697453 Location: Mulgrave Employment Type: Full-time Duration: Fixed-term from December 2026 until September 2027 Remuneration: $110,527 – $121,227 pa HEW
-
Communications Coordinator Job No.: 697174 Location: Alfred Campus Employment Type: Part-time, fraction (0.4) Duration: 12-month fixed-term appointment Remuneration: $100,155 - $108,106 pa HEW Level
-
Vision-Language-Action (VLA) models are changing the way robots perceive their surroundings, interpret instructions, reason about tasks, and interact with the physical world. By bringing vision
-
Manager, Safer Community Unit Job No.: 695338 Location: Clayton campus Employment Type: Full-time Duration: Continuing appointment Remuneration: $145,062 - $153,976 HEW 9 plus 17% employer
-
Research Fellow - Medication, Communication and Engagement in the Community Job No.: 696080 Location: Clayton campus Employment Type: Full-time Duration: 2.5-year fixed-term appointment Remuneration
-
of $37,145AUD per annum 2026 full-time rate (tax-free stipend), indexed plus allowances as per RTP stipend scholarship conditions at: https://www.monash.edu/graduate-research/future-students/scholarships
-
Nick Apostolidis Community Leadership Scholarship Monash Leaders Scholarship This scholarship is intended to support Engineering undergraduate students who come from educationally disadvantaged
-
decisions are made, limiting clinician confidence and adoption in healthcare settings. Large Language Models (LLMs) provide an opportunity to transform explainable AI by translating complex model outputs
-
In EdgeVLMOpt (EVO): Optimizing Vision-Language Models for Resource-Constrained Edge Devices, we aim to develop efficient and scalable techniques to enable the deployment of advanced vision-language
-
, decision-making processes, and even democratic institutions. Large language models (LLMs) have shown tremendous potential in natural language understanding and generation. This research aims to harness