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PhD Opportunity: Data-driven process modelling of pyrometallurgical operations  [November 10, 2022]

Location: Department of Process Engineering, Stellenbosch University, Stellenbosch, South Africa

Scope of Research: In the Extractive Metallurgy and Machine Learning research groups of the Department of Process Engineering at Stellenbosch University, a specific research focus is process monitoring and control for the minerals industry. Statistical and machine learning techniques are explored in the context of dynamic simulation and real-world case studies to investigate promising approaches for cost effective and sustainable operation of mineral processing circuits.

An industrially funded postgraduate opportunity at the PhD level is currently available within the research groups to work on data-driven process modelling of pyrometallurgical operations.

Host: The successful applicant will work under the supervision of Profs Tobi Louw, Guven Akdogan, and Steven Bradshaw.

Requirements and Recommendations:

  • B.Eng in Chemical Engineering (or related field) with a very good academic record as well as an M.Eng in a relevant field.
  • Strong interest in mathematical modelling, statistics, and machine learning.
  • Experience in machine learning techniques such as multi-layer perceptron neural networks and deep learning.
  • Excellent programming skills (preferably in MATLAB and/or Python).
  • The ability to learn independently and take initiative.

Conditions of bursary: Please note that postgraduate students are not appointed as employees and their bursaries are awarded tax free. They are therefore not eligible for employee benefits.

Commencement of studies: Mid-February 2022

Application closing date: 10 January 2022

Enquiries: Please send your CV as well as a cover letter (briefly describing your interest in the project) to Prof Steven Bradshaw (smb@sun.ac.za).

*Stellenbosch University reserves the right not to make an appointment for this position.




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