Faculty of Science

Sensory Evaluation and Food Preferences - Classic and Digital Approaches - 5 ECTS - 2025
Provider: Faculty of Science

Activity no.: 5313-25-04-31
	Enrollment deadline: 15/08/2025

Place

Department of Food Science

Date and time

15.09.2025, at: 12:30 - 19.09.2025, at: 13:00

Regular seats

Activity Prices:

- PhD student (Open Market Agreement, Nova, VLAG)

2,000.00 kr.

- University staff/Non-profit

4,000.00 kr.

- Industry/For-profit

9,000.00 kr.

ECTS credits

5.00

Contact person

Qian Janice Wang E-mail address: qjw@food.ku.dk

Enrolment Handling/Course Organiser

PhD Administration SCIENCE E-mail address: phdcourses@science.ku.dk

Written language

English

Teaching language

English

Exam form

Course Participation; Written Assignment

Exam form

Participation in entire course

Exam details

Class attendance for all course days + course report submission and approval from instructors

Course workload

Course workload category	Hours
Preparation	23.00
Lectures	20.00
Practical exercises	12.00
Theoretical exercises	83.00

Sum	138.00

Content

Enrolment guidelines

The PhD course is a biennial intensive course for PhD students in need of carrying out sensory or consumer acceptance studies as part of their PhD project. The course introduces the foundations of sensory science and practice of performing sensory tests with trained panels and by consumers including their design and execution and assessing sensory and consumer data.

In the 2025 edition of the course, we include the new possibilities of machine learning methods like those based on Natural Language Programming that can be used to enrich sensory and consumer research. Students will have hands-on practice with R programming. Furthermore, we will introduce how AI tools can be used in processing of sensory and consumer data.

The course consists of intensive course days in Copenhagen in addition to a course report on a sensory or consumer food choice behaviour topic related to PhD studies, including a perspective section on the role of machine learning on the chosen topic.

Course content:
Day 1 (half day): Course introduction, the senses and principles of sensory testing
Day 2: Sensory testing in practice: Descriptive analysis and rapid methods with exercises
Day 3: Consumer preferences and beyond: theory and practical exercises
Day 4: Introduction to machine learning and applications of machine learning in sensory research
Day 5: Machine learning in consumer research, course wrap-up (half day)

Formal requirements

Requirements:
- PhD students in need of carrying out sensory or consumer acceptance studies as part of their PhD project. Other researchers from academia/industry also accepted if space allows.
- Short motivation letter (1-2 paragraphs) to explain why they are taking the course and what they expect to get out of the course
• Knowledge of basic statistics
• Basic knowledge of R (otherwise we will give suggested resources to review beforehand)

Learning outcome

Knowledge:
• Understand principles of sensory measurements and evaluation methods
• Understand healthy food preferences in different situational contexts
• Understand common machine learning concepts, including associated algorithms and programmatic tools

Skills:
• Be able to design sensory experiments, analyse and interpret sensory results
• Be able to explore, regress, and classify quantitative and natural language data

Competences:
• Can critically assess literature in the fields of sensory and consumer research.
• Can select appropriate machine learning methodologies for solving research problems in sensory and consumer science.
• Can carry out appropriate sensory and consumer methodologies in own research project.

Literature

Reading materials will be selected for the course by the organisers and the guest lecturers. They will be distributed to the students approximately two weeks before the course.

Target group

PhD students working with sensory or consumer data from all areas, including but not limited to food science, nutrition, biology, agricultural sciences, psychology, neuroscience, marketing

Teaching and learning methods

The course consists of one or two modules:
I. Intensive course program in Copenhagen, Denmark including networking
II. Individual assignment and preparation of a report (deadline 15 November 2025)

Lecturers

>Professor Karin Wendin, Kristianstad University, Sweden
>Associate Professor Qian Janice Wang, University of Copenhagen
>Associate Professor Sébastien Le, Agrocampus Ouest, France
>Dr. Kevin Kantono IFF, The Netherlands
>Professor Lisa Methven University of Reading, UK
>Professor Wender Bredie, University of Copenhagen,

Remarks

The course fee includes course materials, coffee/tea during breaks, lunches and networking dinner. Participants should cover their own expenses of travel and accommodation.

The course fee will depend on the affiliation of the participants as follows:
• PhD students: 2,000 DKK
• Postdoctoral university staff/Non-profit: 4,000 DKK
• Industry/For-profit: 9,000 DKK
Full refund if cancellation latest two weeks before course start.

Co-organisers are Professors Wender Bredie and Karin Wendin

Click the search button to search Courses.

See which courses you can attend and when

Jan	Feb	Mar	Apr
May	Jun	Jul	Aug
Sep	Oct	Nov	Dec