The spring school is now fully booked, but you can still register for the waitlist!

Description

The Spring School provides a comprehensive, tutorial-style, hands-on, introductory and intermediate-level treatment of the essential methods for molecular modelling and computational chemistry using modern supercomputers. The School program is being finalized, but the main content will be similar to last years and consists of:

• Classical molecular dynamics, intro + hands on (1 day)
• Electronic structure theory, intro + hands on (1 day)
• Machine learning in chemistry, intro + hands on
• Enhanced sampling methods, intro + hands on

The school is a must for graduate students in the field, providing an overview of “what can be calculated and how it should be done”, without forgetting the important aspect of network building. The intense schedule is also suitable for industry representatives to get a hands-on introduction to molecular modelling. To get an idea of the depth in which the topics are covered, take a look at the materials from the 2023 School or a blog entry of the 2019 School.

Learning outcome

The learning outcome is to gain an overview of the two main branches of computational chemistry — classical molecular dynamics and electronic structure calculations — in connection with related HPC software packages and other useful skills in the trade. The workshop serves also as an intensive crash course (the first two days) in computational modelling and is expected to be useful for students and researchers in physics, materials science and biosciences as well. The following “Special topics” then build on this foundation.

Another integral aim of the school is to serve as a venue for networking and community building. We have reserved ample time for discussions and interaction, and we highly encourage you to bring a poster to help communicate your work and interests!

Prerequisites

Working knowledge and some hands-on experience in some branch of computational chemistry will be useful. Basic linux skills for hands-on exercises and elementary Python for Machine Learning hands-on. Please consult and prepare with these materials to be able to maximally benefit from the school. During the school, we have only limited support available for elementary command-line / Python issues.

Programme

Tentative agenda

	Wednesday 17 Apr	Thursday 18 Apr	Friday 19 Apr
9-9:15	Welcome & intro	Welcome & intro	Welcome & intro
9:15-10	Introduction to classical MD	Introduction to electronic structure theory	Enhanced sampling methods (lecture)
10-10:15	break	break	break
10:15-11	Intro… continued	Intro… continued	Enhanced sampling methods (lecture / hands-on)
11-11:15	break	break	break
11:15-12	Intro… continued	Intro… continued	Enhanced sampling methods (hands-on)
12-13	lunch	lunch	lunch
13-13:45	MD hands-on: 3 parallel sessions …	QC hands-on: 3 parallel sessions …	Machine learning in chemistry 1 (MD, lecture)
13:45-14:30	…basic, inter, advanced	…basic, inter, advanced	Machine learning in chemistry 1 (MD, hands-on)
14:30-14:45	break	break	break
14:45-15:30	MD hands-on: continued	QC hands-on: continued	Machine learning in chemistry 2 (QC, lecture)
15:30-16:15	MD hands-on: continued	QC hands-on: continued	Machine learning in chemistry 2 (QC, hands-on)
16:30-19:00	Poster session + snacks	Sauna talk…	Closing (15 min)
18:30-22:00		…and sauna + dinner

Software used in the School

GROMACS, Turbomole, CP2K, Python, etc.

Participation fee

The spring school is now fully booked, but you can still register for the waitlist!

The school has a participation fee of 120 EUR (+ VAT). It covers the lectures, coffees, lunches, poster session snacks, and the sauna + dinner. A small fee is necessary to cover a part of the costs and to reduce no-show as only limited seats are available.

Please briefly describe your background, skills, and expectations upon course application. The registration deadline is at 17th of March 2024, but as the course is likely to be fully booked, we recommend you to reserve your seat early. A waiting list will be used in case of cancellations.

While CSC cannot guarantee credits, as the decision is finally up to your own institute, we’ll supply a certificate which recommends granting 1 ECTS credits for each participant.

Lecturers

• Prof. Antti Karttunen, Aalto University, Finland
• Prof. Milica Todorović, University of Turku, Finland
• Dr. Hector Martinez-Seara, Czech Academy of Sciences, Czech Republic
• Dr. Matti Javanainen, University of Helsinki, Finland
• Dr. Shreyas Kaptan, University of Helsinki, Finland
• Dr. Atte Sillanpää, CSC-IT Center for Science, Finland
• Dr. Nino Runeberg, CSC-IT Center for Science, Finland
• Dr. Rasmus Kronberg, CSC-IT Center for Science, Finland
• Dr. Xavier Prasanna, CSC-IT Center for Science, Finland

Funding

The course is organized with support from and as a collaboration between CSC, EuroCC2 and BioExcel3.