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Lecturer: Data Science

Job Summary
One position is advertised for academically strong candidates to join the Data Science Research Group (DSRG) of the Department of Industrial Engineering to advance data science research and teaching.

Stellenbosch University

Department of Industrial Engineering

Lecturer: Data Science

Ref. ING01/145/0624

The Department of Industrial Engineering at Stellenbosch University (SU) is a research-intensive department, focusing on the following areas of research to improve global competitiveness: Operations Research, Data Science in Industrial Engineering; Operations Management and Logistics; Advanced Manufacturing; and Engineering and Technology Management.

One position is advertised for academically strong candidates to join the Data Science Research Group (DSRG) of the Department of Industrial Engineering to advance data science research and teaching. The incumbent will be expected to keep abreast of the latest research in specific data science specialisations as listed below, as well as academic content and practical applications within data science. The DSRG focuses on the science of data science, under the guidance of an A-rated researcher, as well as the application of data science in the industrial engineering domain. The position is on lecturer level.

The position is for a permanent appointment tailored for academically strong candidates wishing to pursue an academic career in data science, with:
  • A relevant PhD, or
  • A master's degree with at least threeyears' relevant technical or research experience in a specific technical field of expertise with a commitment to enrol for a PhD in a data science related field.

     

    Reporting to a senior researcher from the Department in the above area of specialisation, the incumbent will perform or assist with research, study leadership, and lecturing duties on undergraduate and postgraduate level.

    Duties:
    Specific duties will include, although will not be limited to:
    • Assisting with the academic guidance and management of the DSRG;
    • Undergraduate, postgraduate and short course teaching in data science and related subjects;
    • Providing guidance and leadership to postgraduate students and undergraduate project students;
    • Conducting research in data science and technology transfer to and from industry;
    • Creating and participating in the application of research grants.
    Requirements:
    • On undergraduate level, an appropriate undergraduate qualification in engineering or computer science;
    • A master's degree in a data science-related discipline with research experience in data science (or the application thereof), but with specific focus in at least two of the following areas of specialisation: machine learning, MLOps, evolutionary learning, explainable artificial intelligence, machine learning approaches for data mining, and/or the application of any data science related field in Industrial Engineering;
    • An excellent academic record (please include a transcript of all undergraduate and postgraduate achievements to date);
    • Experience in teaching and assessment of modules in data science in engineering and/or computer science undergraduate and postgraduate curriculums, specifically in the above listed data science specialisations;
    • Experience in supervision of students in undergraduate data science projects;
    • Good verbal and written communication skills in English;
    • Strong commitment to becoming a scholar in data science, specifically in the above data science specialisations;
    • Strong programming experience.

    (Kindly note the requirements for the cover letter, in which you should detailyour adherence to each of these requirements.)

    Recommendations:
    • With reference to data science disciplines, teaching and research experience in deep learning or ig Data platforms and architectures, federated learning;
    • Scholarly achievements in any of the above data science specialisations, to include journal (Q1 and Q2 journals) and mainstream conference publications;
    • Evidence of involvement with academic activities, including reviews for journals and/or conferences;
    • Track record of hands-on experience in deploying and maintaining machine learning models in production;
    • Experience with machine learning deployment frameworks, including containerisation, serverless architecture and other deployment strategies;
    • Experience in testing and monitoring models in production, e.g. monitoring models for performance issues, data drift, and other potential problems;
    • Knowledge of software engineering best practices and how they apply to machine learning;
    • Experience with cloud-based machine learning services such as AWS, Azure Machine Learning, or Google Cloud API Platform;
    • Experience in deploying machine learning models on Edge;
    • Proficiency in English and Afrikaans.

    Commencement of duties: 01 October 2024 or as individually negotiated

    Closing date: 15 July 2024

    Enquiries regarding this post: Prof Joubert van Eeden on 021 808 4234, or at jveeden@sun.ac.za

    Enquiries regarding remuneration/benefits, as well as technical assistance with the electronic application process: Human Resources Client Services Centre on 021 808 2753, or at sun-e-hr@sun.ac.za

    The University is committed to employment equity (EE), and appointments will be made in line with the EE plan for the specific environment as well as Stellenbosch University's institutional EE Plan.

    Stellenbosch University reserves the right not to make an appointment.

    Your application, comprising a comprehensive curriculum vitae (including the names and e- mail address of at least three referees) and a cover letter with detail on adherence to the requirements and recommendations, must reach the University before or on the closing date of the advertised post.

    APPLY ONLINE AT https://www.sun.ac.za/english/careers BY USING THE APPLY NOW LINK AT THE TOP RIGHT-HAND CORNER OF THE SPECIFIC VACANCY PAGE.

    The University reserves the right to investigate qualifications and conduct background checks on all candidates.

    Should no feedback be received from the University within four to six weeks of the closing date, kindly accept that your application did not succeed.

Job Location
 

South Africa University Jobs
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