Underwater R&T Intern

Location: Singapore, Singapore

In fast changing markets, customers worldwide rely on Thales. Thales is a business where brilliant people from all over the world come together to share ideas and inspire each other. In aerospace, transportation, defence, security and space, our architects design innovative solutions that make our tomorrow's possible.

Thales established its presence in Singapore in 1973 to support the expansion of aerospace-related activities in the Asia-Pacific region. Throughout the last four decades, the company grew from strength to strength and is today involved in the primary businesses of Aerospace (including Air Traffic Management), Defence & Security, Ground Transportation and Digital Identity & Security. Thales today employs over 2,100 people in Singapore across all its business areas.

TOPIC : Identify and Locate Objects Automatically in 2D Greyscale Images of Shadows

Description

We are developing a proof-of-concept (POC) demonstration system of an AI classification system to identify and locate objects in 2D greyscale images of shadows. The challenge in this case is that only the shadow of the objects projected on the ground is clearly visible, the objects themselves have limited visibility due to (1) the absence of color (2) only top view is given. The work involves entire machine-learning lifecycle including data exploration, data preparation (cleaning / transforming / annotation), feature selection, model training / testing and model tuning / selection.

Specific Responsibilities

• Set up the computing hardware / software from scratch
• Collect / clean / transform / annotate data
• Survey / select / develop / compare candidate AI models
• Develop software codes to automate model training / testing / tuning / selection

Key Requirements

• Working knowledge in entire machine-learning lifecycle
• Experience in any scripting language e.g. shell, Python, Matlab
• Preferably experience in API calls e.g. HTTP, command line, linked library
• Team player

Expected Outcomes

• Demonstration of a working system with well-defined end-to-end test scenarios
• Documentation of the finding, design and test cases / results
• Team sharing and communication of various forms, including but not limited to live demo, video and workshops

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