Georgia Institute of Technology

What you'll study

The programme emphasises experimental design, statistical literacy and hands-on research experience alongside core psychological theory. Early coursework covers foundational topics such as biological bases of behaviour, learning and cognition, social and developmental psychology, and research methods. Quantitative and computational skills are central: students typically take courses in statistics for the behavioural sciences, multivariate methods, and programming for data analysis.

• Core modules: Introduction to Psychology, Biological Psychology, Cognitive Psychology, Social Psychology, Developmental Psychology.
• Research and methods: Research Methods in Psychology, Experimental Design, Statistics for Psychology, Advanced Data Analysis, Psychometrics.
• Specialist/advanced topics: Cognitive Neuroscience, Perception, Learning and Memory, Decision Making, Emotion and Motivation.
• Computational and technical training: Programming for behavioural research, computational modelling, neuroimaging methods (where available).
• Capstone and independent research: Senior thesis or honours project involving supervised laboratory research, plus laboratory practicum or internship opportunities.

Students are encouraged to engage in research from early in the degree through lab placements and faculty-led projects. The curriculum is designed to integrate psychological theory with empirical practice, emphasising reproducibility, data management and ethical research conduct.

Entry requirements

Applicants need a high school diploma or equivalent with strong academic performance. Georgia Tech is a selective institution; successful applicants typically demonstrate solid preparation in mathematics and the sciences. Recommended preparation includes:

• High school mathematics through calculus or evidence of quantitative competency.
• Strong grades in science and social science courses; prior psychology study is helpful but not mandatory.
• Demonstrable analytical skills and extracurricular engagement in research, labs, internships or related activities strengthen an application.

International applicants must hold an equivalent secondary qualification and meet the institute's English language proficiency requirements. Admissions decisions are based on the overall academic record and the competitiveness of the applicant pool; consult Georgia Tech's admissions office for specific application procedures and documentation requirements.

Career prospects

Graduates are prepared for research-focused roles and for further study. Typical career pathways include:

• Research assistant or coordinator in academic, government or private research labs.
• Data analyst, behavioural scientist or market researcher using quantitative and experimental skills.
• User experience (UX) researcher, human factors specialist or product researcher working at technology companies.
• Clinical, counselling or school psychology careers following graduate study and appropriate professional training.
• Progression to graduate programmes (Master’s or PhD) in psychology, cognitive neuroscience, computational modelling, or neighbouring disciplines; some graduates also pursue professional degrees (e.g. medicine, public health).

The degree’s strong methodological and computational emphasis makes alumni attractive to employers in tech, healthcare, education, government and industry research settings.

Why study at Georgia Institute of Technology

Georgia Tech combines a rigorous STEM culture with robust psychological science, giving students an applied, quantitative approach to behaviour and cognition. The department offers opportunities to work with faculty on active research projects and to access interdisciplinary collaborations with engineering, computer science, neuroscience and public policy units across campus.

Students benefit from hands-on laboratory experience, training in contemporary data analysis techniques, and pathways to internships with technology firms and research institutions in the region. The programme’s emphasis on experimental design and computational skills prepares graduates for both immediate employment and competitive graduate-level study.