Graduate School of health and Medical Sciences

Hackathon – application of machine learning in biomedical research - Part B
Provider: Faculty of Health and Medical Sciences

Activity no.: 3927-22-00-00
	Enrollment deadline: 25/04/2022

Date and time	07.06.2022, at: 09:00 - 10.06.2022, at: 17:00
Regular seats	24
Course fee	2,520.00 kr.
Lecturers	Ruth Loos
ECTS credits	3.20

Contact person	Imke Thiessen E-mail address: imke.tiessen@sund.ku.dk

Enrolment Handling/Course Organiser	PhD administration E-mail address: phdkursus@sund.ku.dk

Aim and content This is a generic course. This means that the course is reserved for PhD students at the Graduate School of Health and Medical Sciences at UCPH. Anyone can apply for the course, but if you are not a PhD student at the Graduate School, you will be placed on the waiting list until enrollment deadline. After the enrolment deadline, available seats will be allocated to the waiting list. The course is free of charge for PhD students at Danish universities (except Copenhagen Business School), and for PhD students at graduate schools in the other Nordic countries. All other participants must pay the course fee. Learning objectives A student who has met the objectives of the course will be able to: 1. Apply machine learning to biological and medical datasets 2. Apply python machine learning modules 3. Evaluate the performance of machine learning systems 4. Disseminate the project results in a technical report Content Hackathon - Application of machine learning in biomedical research (4 days) Days1 to 3 Work + invited (virtual) speaker Project work Reporting back Day 4 Final presentations Report writing After the course: Submission of final report. Participants Participation in the 5-day course 'Introduction to machine learning in biomedical research' (Course code: 3926-22-00-00) is a prerequisite to attend this course. PhD students enrolled at the Graduate School of Health and Medical Sciences and postdocs at specific Centers/Departments with some experience in Python programming. Max 24 participants Relevance to graduate programmes The course is relevant to PhD students from the following graduate programmes at the Graduate School of Health and Medical Sciences, UCPH: All graduate programmes Language English English or Danish. Note that all courses have to be provided in English if required by non-Danish participants. Form Lectures, seminars, group work, discussions, exercises, project work. Course director Ruth Loos, Professor, Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, ruth.loos@sund.ku.dk Anders Krogh, Professor, Section for Computational and RNA Biology, Department of Biology, University of Copenhagen, anders.krogh@sund.ku.dk Cameron MacPherson, Group Leader, CHIP, Centre of Excellence for Health, Immunity and Infections, cameron.macpherson@regionh.dk Teachers Anders Krogh, Professor, Section for Computational and RNA Biology, Department of Biology, University of Copenhagen Shyam Gopalakrishnan, Associate Professor, Section for Evolutionary Genomics, GLOBE institute, University of Copenhagen Thomas Moritz, Professor, Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen Tune H Pers, Associate Professor, Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen Mani Arumugam, Associate Professor, Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen Simon Rasmussen, Associate Professor, Novo Nordisk Foundation Center for Protein Research, University of Copenhagen Ramtin Zargari Marandi ramtin.zargari.marandi@regionh.dk External lecturers Ole Winther, Professor, Department of Applied Mathematics and Computer Science, DTU Dates Hackathon - hands-on projects June 7, 8, 9, 10, 2022 Course location PANUM Maersk Tower Blegdamsvej 3B, 2200 Copenhagen Floor 15, room 7.15.152 Registration Please register before April 25, 2022 Seats to PhD students from other Danish universities will be allocated on a first-come, first-served basis and according to the applicable rules. Applications from other participants will be considered after the last day of enrolment. Note: All applicants are asked to submit invoice details in case of no-show, late cancellation or obligation to pay the course fee (typically non-PhD students). If you are a PhD student, your participation in the course must be in agreement with your principal supervisor.

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