Associate Lecturer in Quantitative Research Methods
Teach advanced statistical analysis (ANOVA, experimental design) in BSc Psychology at a leading UK university.
Best for:Best for psychology graduates with a PhD or significant research experience, strong teaching skills in higher education, and expertise in quantitative methods (ANOVA, experimental design).
Overview
This part-time, fixed-term role at Birkbeck, University of London, involves delivering a core module on quantitative research methods to undergraduate Psychology students. The position focuses on experimental design, ANOVA techniques, and data analysis, with full teaching materials provided. The successful candidate will collaborate with module convenors to organise, teach, assess, and administer the module, which is a compulsory component of the BPS-accredited BSc Psychology programme. The role is ideal for psychology graduates with teaching experience in higher education, particularly those familiar with adult learning and statistical analysis.
What you'll do
- Deliver 10 teaching sessions (3 hours each) on quantitative research methods, covering ANOVA, experimental design, and data analysis.
- Prepare and deliver lectures, workshops, and assessments for undergraduate Psychology students.
- Administer and grade student work, including assignments and exams.
- Collaborate with module convenors to organise teaching schedules and coordinate module delivery.
- Engage with full- and part-time adult learners, tailoring teaching methods to their needs.
- Use digital platforms like Moodle and Teams for course administration and communication.
Requirements
Degree required: Degree in Psychology or related field; pursuing or completed a PhD in Psychology or a related area.
Language: English; proficiency appropriate for teaching in a UK university setting.
Instruction: English
- Proven teaching experience in higher education, particularly with adult students.
- Strong understanding of experimental design and ANOVA techniques.
- Experience with statistical analysis and data visualization.
- Familiarity with IT tools including Word, Excel, Moodle, and Teams.
- Excellent communication, interpersonal, and presentation skills.
- No specific nationality or residency restrictions mentioned.
- Experience or willingness to develop a wide range of teaching and assessment methods.
Funding & terms
How to apply
Deadline: 2026-11-01
Submit a CV for consideration through the university’s application portal. Interviews will be held on November 18, 2026. For further inquiries, contact Silvia Seghezzi, module convenor, via email.
- CV
Contact
Silvia Seghezzi· Module Convenor
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