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MEIN40430

Academic Year 2025/2026

Internship research project 20 (MEIN40430)

Subject:
Medical Informatics
College:
Health & Agricultural Sciences
School:
Medicine
Level:
4 (Masters)
Credits:
20
Module Coordinator:
Dr Vadim Zhernovkov
Credit Split by Trimester:
Spring 10
Summer 10
Trimester:
2 Trimester duration (Spr-Sum)
Mode of Delivery:
On Campus
Internship Module:
Yes
How will I be graded?
Letter grades

Curricular information is subject to change.

Students will complete a work placement in a research group in UCD or Irish hospitals. The aim of this module is to provide hands-on experience in data analysis using real-life problem-solving projects in collaboration with our academic and clinical partners. It will use machine learning methods provided in the core curriculum for the MSc AI for Medicine and Medical Research. Following the internship, the students will prepare a report on their project and make an oral presentation.
This module has limited capacity and entry is competitive.

About this Module

Learning Outcomes:

During the placement the student will undertake various research related tasks that may include data pre-processing, inputting and managing data, differential gene/protein expression analysis, pathway and network analysis, machine learning analysis, biological interpretation of results. The module will provide hands-on experience in data analysis using real science projects in collaboration with our academic and clinical partners.

Student Effort Hours:
Student Effort Type Hours
Lectures

0
Placement/Work Experience

500
Total

500

Approaches to Teaching and Learning:
Students will complete a work placement in a research group in UCD or Irish hospitals. The aim of this module is to provide hands-on experience in data analysis using real-life problem-solving projects in collaboration with our academic and clinical partners. It will use machine learning methods provided in the core curriculum for the MSc AI for Medicine and Medical Research. Following the internship, the students will prepare a report on their project and make an oral presentation.

Requirements, Exclusions and Recommendations

Not applicable to this module.


Module Requisites and Incompatibles
Additional Information:
This module requires significant prior programming experience in R or Python


 

Assessment Strategy
Description Timing Component Scale Must Pass Component % of Final Grade In Module Component Repeat Offered
Report(s): Students should provide a written report and present the project in a seminar Week 15 Summer Graded No
100
 No

Carry forward of passed components
Yes
 

Remediation Type Remediation Timing
In-Module Resit Prior to relevant Programme Exam Board
Please see Student Jargon Buster for more information about remediation types and timing. 

Feedback Strategy/Strategies

• Feedback individually to students, post-assessment
• Group/class feedback, post-assessment

How will my Feedback be Delivered?

Not yet recorded.

Name Role
Dr Luis Fernando Iglesias Martinez Lecturer / Co-Lecturer
Anastasiia Korosteleva Tutor
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