Job Description

Job Summary

Nelson Mandela University reserves the right not to make an appointment. In considering candidates for appointment into the advertised posts, preference will be accorded to persons from a designated group in accordance with the approved Nelson Mandela University Employment Equity Plan.

CORE PURPOSE OF JOB

The objective of the Department of Statistics at Nelson Mandela University is to produce graduates who, by facilitating the advancement of statistical knowledge and using their statistical training, will contribute positively to the development of South Africa and society.

The core purpose of this post is to facilitate and coordinate the learning process of undergraduate and postgraduate students in the statistics department, to engage in research activities, contribute to community engagement and to be involved in the advancement of the core initiatives of the department.

More specifically, it is expected that the successful candidate has a well-defined and established research focus area within the mathematical statistics discipline (with national and international recognition). The candidate will be expected to lead the development of this area within the department, through the generation of knowledge (teaching), accredited research outputs and supervision of postgraduate students and post-docs in this area.

KEY PERFORMANCE AREAS

• To facilitate and coordinate undergraduate and postgraduate teaching and learning in the department.
• Develop teaching/learning materials to ensure that relevance and quality are maintained.
• Obtain research grants and secure research funding for their research area.
• To engage in inter-departmental and/or inter-faculty collaborative research to generate cross-disciplinary engagement and research outputs.
• Regularly contribution to knowledge generation in the mathematical statistics field by conducting and publishing accredited research outputs in statistics focussed journals.
• To supervise honours, masters, PhD and post-doc students in the department.

• Take the lead in development of academic programmes, curriculum development, evaluation, and revision.
• Be prepared to serve as the Head of Department for a defined period.
• Serve on committees relevant to the department and partake in departmental activities.
• Engage with the broader statistical community.

CORE COMPETENCIES

• Possess expert knowledge of the theory and application of Mathematical Statistics and the ability to cope with a changing teaching environment and be adaptable to evolving situations.
• Have extensive experience at facilitating learning at all levels and be able to coordinate the teaching of large classes and postgraduate programmes.
• Possess the academic ability and personality to teach at all levels up to and including PhD.
• Possess excellent communication skills to engage internal and external stakeholders in departmental endeavours.

• To be able to lead the departmental research and teaching activities in their area of expertise and be able to develop and implement their own research programme in this area.

• Be able to carry out independent research and act as principal investigator and project leader.
• Possess excellent communication skills for both teaching and report writing.
• Make regular contributions to the body of knowledge through DHET accredited publications in statistics focused national and international journals.
• Actively engage with the statistics community through participation in and presentation at national and international conferences.
• To be reliable, responsible, dependable and to fulfil obligations and be cooperative with others.
• Have expert knowledge and competence in one or more statistical software package (R, SAS, SPSS, Python etc).

REQUIREMENTS

• A PhD degree (on NQF Level 10) in Mathematical Statistics or Statistics.

• At least five (5) years lecturing and teaching experience at an institute of higher education in the position of associated professor, with demonstrated experience in undergraduate and postgraduate teaching in the field of Statistics and/or Mathematical Statistics.
• Demonstrated successful supervision of graduated doctoral students, with experience as an external examiner of postgraduate research at all levels.
• Have a proven track record of regular DHET accredited publications and conference presentations - meeting the requirements of a NRF C rated researcher (at least).
• Meeting the following will be advantageous:

• PhD degree in the Mathematical Statistics Discipline.
• Proven national recognition for specialist expertise and research leadership in a particular area academic scholarship within the Statistics and/or Mathematical statistics discipline.
• Having been invited and delivered keynote/plenary addresses at scholarly conferences in the Statistics and/or Mathematical Statistics discipline.
• Being the current holder of a C2 or higher NRF rating.

ADDITIONAL INFORMATION

CLOSING DATE FOR APPLICATIONS:

Note: Candidates invited to an interview will be expected to demonstrate their ability to lecture by presenting a 10-minute lecture on a topic which will be communicated to them prior to the interview. Candidates may be expected to demonstrate their statistical software skills to support their application.

Each application must include:

• a letter of motivation indicating the candidates suitability for the post;
• a current curriculum vitae (only include DHET accredited research outputs) with the names and full contact details of at least three referees;
• certified copies of qualifications;
• a complete teaching portfolio.

Nelson Mandela University

University Way Summerstrand

2-10

Company

About

Vision To be a dynamic African university, recognised for its leadership in generating cutting-edge knowledge for a sustainable future. Mission To offer a diverse range of quality educational opportunities that will make a critical and constructive contribution to regional, national and global sustainability. Values Respect for diversity,Excellence,Ubuntu,Integrity,Respect for the natural environment,Taking responsibility

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