Total 4 pr agent job vacancies in Education / Training category in Singapore

The Continental-NTU Corp Lab invites applications for the position of Research Fellow.

Key Responsibilities:

• Develop optimization, control, learning, coordination, and/or management solutions to support multi-robot coordination and fleet management
• Programming and testing of the developed models, algorithms, and methods
• Write the research results into publication manuscripts and project reports
• Contribute to project reporting and demonstration

Job Requirements:

• PhD in Electrical Engineering, or Automation, or Computer Science and Engineering, or related disciplines from a prestigious university
• Have at least 1 first-author publication in top-tier journal
• Knowledge in at least one of the following topics: multi-robot coordination, fleet management, optimization, control, and learning, or robotics
• Good simulation and programming skills
• Good interpersonal skills
• Good communication and writing in English

We regret that only shortlisted candidates will be notified.

The Continental-NTU Corp Lab invites applications for the position of Research Fellow.

Key Responsibilities: 

• Develop optimization, control, learning, coordination, and/or management solutions to support multi-robot coordination and fleet management

• Programming and testing of the developed models, algorithms, and methods

• Write the research results into publication manuscripts and project reports

• Contribute to project reporting and demonstration

Job Requirements:

• PhD in Electrical Engineering, or Automation, or Computer Science and Engineering, or related disciplines from a prestigious university

• Have at least 1 first-author publication in top-tier journal

• Knowledge in at least one of the following topics: multi-robot coordination, fleet management, optimization, control, and learning, or robotics

• Good simulation and programming skills

• Good interpersonal skills

• Good communication and writing in English

We regret that only shortlisted candidates will be notified.

Job Description

The Continental-NTU Corporate Lab invites applications for the position of Research Fellow.

Continental-NTU Corporate Lab is a S$50 million joint corporate laboratory between NTU and Continental that focuses on developing technologically advanced solutions in the areas such as autonomous robotics, navigation, artificial intelligence (AI), cybersecurity, smart materials, sensing, communication, and cloud technologies for future urban mobility applications. We aim to accelerate innovation in Singapore’s automotive industry and translate research outcomes into practical and viable urban mobility solutions for the future.

Key Responsibilities:

• Develop multi-agent control optimization or learning methods for multi-robot coordination and fleet management.
• Conduct simulation assessment and demo of the developed methods.
• Write the research results into publication manuscripts, patents, and/or project reports.

Job Requirements:

• PhD in Optimization and game theory, or Control, or AI, or Robotics.
• Have at least 1 first-author publication in top-tier journals in related areas.
• Good interpersonal skills.
• Good communication and writing in English.
• Good teamwork awareness.

We regret that only shortlisted candidates will be notified.

Interested applicants are invited to apply directly at the NUS Career Portal.

Your application will be processed only if you apply via NUS Career Portal.

We regret that only shortlisted candidates will be notified.

Job Description

This project will focus on the multi-agent search problem, where multiple autonomous robots (agents) are tasked with spreading over a given region to be explored, to locate given targets of interest trying to evade detection. The number of targets is unknown, and their initial position is not known as well. There might be obstacles in the domain, and their location might or might not be known. Throughout this work, we will assume that robots can communicate their observations (presence/absence of targets) during search, via local or global communications, so they can update their representation of the domain and likely location(s) of targets (more details about this representation in the next Section). Our goal is to allow robots to plan efficient search paths to cover the domain and localise the targets as quickly as possible, while relying on local sensing and on distributed intelligence rather than on centralised planning, which would represent a vulnerable bottleneck and would not scale well to large agent teams.

Qualifications

• Excellent coding skills in python with pytorch (distributed deep reinforcement learning, Transformers, etc.)
• Literature review/summarizing skills
• Simulations abilities (e.g., AirSIM, ROS Gazebo)
• Experience with implementation of deep learning model on hardware (e.g., ground/aerial robots)
• Experience publishing papers, and supervising undergraduate/master’s students