LECTURER (DATA SCIENCE/MACHINE LEARNING
Job Title LECTURER (DATA SCIENCE/MACHINE LEARNING) Two Positions
Location Braamfontein,ZA
Organization Name School of Computer Science and Applied Mathematics
Description: The School of Computer Science and Applied Mathematics undertakes high quality research in a wide variety of areas and is home to several National Research Foundation (NRF) rated scientists. In the domain of Computer Science, the School’s main research areas include machine learning, big data analytics, computer vision, high-performance computing, robotics, scientific computing, formal languages and automata, natural language processing and logic. We seek applicants with some experience in research, tertiary teaching and postgraduate supervision in the areas of data science, computational statistics, applied and theoretical machine learning and large-scale computing.
Brief Description
Qualifications: Applicants must hold a doctorate in Computer Science or related fields and have evidence of teaching experience at a tertiary institution. Individuals with research interests in machine learning, or data science or big data analytics will be preferred. Furthermore, the applicant must have evidence of research and publications in recognized conferences, journals and/or scholarly books. Further, evidence of postgraduate supervision is necessary, while evidence of academic citizenship (University administration) and a South African NRF rating are advantageous (if available).
Duties: The successful applicant will be expected to teach machine learning and big data related courses, at undergraduate and postgraduate levels, supervise and/or co-supervise postgraduate students, participate in academic administration and develop a productive research programme.
HOW TO APPLY
To apply: External applicants are invited to apply by registering their profile on the Wits iRecruitment platform located at https://irec.wits.ac.za and submitting applications. Internal employees are invited to apply directly on Oracle by following the path: iWits /Self Service application/”Apply for a job”.
Correspondence will be entered into with short-listed candidates only. Short-listed applicants must be available for a personal or telephonic/Skype interview, and the presentation of a short lecture on a topic decided by the Head of School and a seminar on the proposed line of research may be required.
CLOSING DATE: 30 NOVEMBER 2022
“The University is committed to employment equity. Preference may be given, to appointable applicants from the underrepresented designated groups in terms of the relevant employment equity plans and policies of the university. The University retains the right not to make an appointment and to verify all information provided by candidates”.
