Computing Internship - Envir AI Pty Ltd

This position is offered through the ANU Computing Internship

Company

At Envir AI we have developed a working system that enables non-AI experts to configure, optimise and operate machine learning, currently paying customers using this for image processing.

Project Title 

Blending of Symbolic with Neural AI

Project description

Developing a basic ontology for a domain and map a pre-labelled dataset to the ontology.

The student will then run a series of experiments with various labelling strategies and explore the impact of how ontological labelling improves Neural output and Neural explainability.

This project is suited to students with a python programming background, who want to explore bringing together two distinct aspects of AI and explore how they could be integrated. The work will be on real world data and machine learning infrastructure build by us.

Required/preferred technical skills or experience in software languages, environments, platforms.

Python, Interest in Reasoning systems and machine learning.

Delivery Mode

Remote (Intern engages on project in a remote capacity)

Yes, we are happy to host a student residing in any location

Eligibility

This internship is available to all eligible students. No citizenship requirements apply.

How to apply

Applications are invited from eligible students to apply for the Computing Internship courses COMP3280 or COMP8830. Eligibility details and further information about the Computing Internship can be found on the Computing Internship page

1. Students must first seek confirmation of eligibility by submitting an Eligibility and Room Available in degree check.  

2. Eligible students can then apply through the Computing Internship application form. You can nominate multiple preferred Internship placements through the one application form. 

Applications for Round 1 open on 20 September and close on 30 September 2021.

Application closing date

30 September 2021
Applications open for this opportunity: 
15 Sep 2021
Study level: 
Postgraduate
Undergraduate
Student opportunity type: 

Updated:  10 August 2021/Responsible Officer:  Dean, CECS/Page Contact:  CECS Marketing