We are seeking to appoint a software engineer with expertise in C++ programming. The position is casual/ hourly basis and is expected to continue for 6 months. The programmer will be developing a simulation model of passengers' movements in a train station using an already developed open source tool PEDSIM (pedsim.silmaril.org). This will involve extensive programming in C++.
The position will be based in the Department of Civil Engineering and will involve interaction with the other collaborators from Institute of Railway Technology and the Department of Design at Monash University. You will work closely with Dr Meead Saberi and the research team.
To be successful you must have a Bachelor or Master's degree in software engineering, information technology or a relevant field and will possess sound interpersonal skills, along with excellent written and oral communication abilities. You must have solid experience and proven skills in C++.
If you believe you fit this profile, we look forward to receiving your application. To apply, please email your full CV including your previous experience in C++ programming to email@example.com.
Talk Abstract: Big data sources such as smartphones, mobile devices, social media and ubiquitous sensors allow us to collect data with details and coverage unimaginable before. These datasets show us the importance of considering dynamics in urban modeling. Transportation systems research can exploit these vast data sources to a great extent. The overarching goal of this work is to develop data analytics to understand urban dynamics and user behavior using geo-located social media data. Novel statistical estimation techniques are developed to understand the spatiotemporal patterns of urban activities based on more than half a million Foursquare check-ins of about 20,000 users from New York City. A novel method is developed to infer activity type, its duration and location, and the sequence of the activities from incomplete trajectory data. When aggregated these activity-location sequences indicate the travel demand within a region. The potential of geo-location data to derive dynamic traffic patterns is demonstrated by building an agent-based simulation model. Potential applications of these techniques to a number of urban systems science challenges are also outlined.
From left to right: Sajjad, Meead, Richard, and Frank.
Location: Boost Juice, Campus Centre, Clayton campus
I am happy to launch the new website of my research lab, CityX which was formerly known as City Science. CityX website is hosted outside Monash University and is intended to serve as my main communication channel with my students, the research community, and public. The new website is better organized, easier to navigate and a lot better in loading.