The MUST Deep Learning research group performs basic and applied research in machine learning, with an emphasis on the theory and application of deep learning. MUST is a member of the Centre for Artificial Intelligence Research (CAIR), and the coordinator of the ‘Machine Learning in support of theoretical and computational science’ research programme of the National Centre for Theoretical and Computational Science (NITheCS). As such, the group is responsible for developing specialised machine learning (ML) techniques and applying these for scientific applications with a network of collaborating researchers.  

The purpose of this position is to be the lead software developer on selected machine learning research and development (R&D) projects in MUST, and to assist with technical leadership and project team coordination of related projects. A main priority of the incumbent will be to support the NITheCS project mentioned above, by contributing to the software development of a suite of deep learning tools that support knowledge discovery from time series data.

1.      DEVELOPMENT:

·       Design and development of software incorporating advanced deep learning algorithms and analysis techniques

2.      LEADERSHIP:

·       Lead and coordinate related software development projects

·       Conduct research regarding client needs and possible solutions

4.      CLIENT LIAISON:

·       Liaise with external clients and collaborators on related projects.

5.      ADMINISTRATION:

·       Participate in MUST support activities, as required.

·       A Master’s degree in Engineering or Computer Science.

·       Two years of experience in machine learning.

 

·       Decision-making skills

·       Analytical and problem-solving skills

·       Leadership skills

·       Self-motivation

·       Critical thinking

·       A theoretical understanding of deep neural networks and their generalisation ability is essential.

·       A theoretical understanding and practical experience in the application of interpretability techniques to DNN architectures is a decided advantage.

·       Advanced computer literacy skills and proficient in the use of Linux operating systems.

·       Strong programming and/or scripting skills, especially using Python.

·       Experience in using scientific and advanced machine learning toolkits. Experience in using numpy, pandas, PyTorch is a specific advantage.

·       Good technical writing and communication skills.

The annual total remuneration package will be commensurate with the level of appointment as advertised and in line with the NWU policy guidelines.