Introduction

[CHRISTINA-ANNA GATSIOU]

Hi everyone,

     I am Christianna Gatsiou, currently a software engineer for a company manufacturing biomedical imaging systems. I have very good knowledge of C++, Python and extended experience in developing software for scientific applications.

     I have received my PhD from Imperial College London in the field of Crystal Structure Prediction where I performed computational studies for a range of organic crystals using a variety of modelling  methods from atomistic to quantum mechanical and developed a parameter estimation algorithm to improve current (force fields) for organic molecular crystals.

     Prior to my current position I was a research fellow at the NCSR Demokritos in Athens, Greece working on atomistic and coarse-grained simulations of nanocomposites and I am familiar with the molecular simulations software LAMMPS, GROMACS, and VOTCA.

     I would be interested to be involved in the MDAnalysis project and particularly with the group generalisation project.

Best regards,

Christianna

[Project Manager MDAnalysis]

Hi Christianna,

Welcome to MDAnalysis! 

MDAnalysis is a Python package for the analysis of computer simulations of systems at the atomic scale. We have a few introductory videos that can give you an idea of what problems MDAnalysis is solving.

The best way to get started is to get your hands dirty following the MDAnalysis User Guide. We suggest starting with installing the MDAnalysis package and going through the Quick Start Guide. Other sections of the User Guide go into many more details about the different capabilities of MDAnalysis.

Once you are a bit familiar with the MDAnalysis package, you can look at the sections of the User Guide explaining how to contribute. There are detailed explanations on how to set up a developer environment and how to contribute to the MDAnalysis codebase. This is a great starting point for contributing to MDAnalysis and trying to solve some of the open issues.

Our blog post is the starting point for all GSoC 2023 things, and we have a FAQ. As per the FAQ, candidates must have code merged to be eligible to apply to GSoC with MDAnalysis. On the MDAnalysis repository, you can find several issues tagged with "good first issue", "Difficulty easy", or "GSoC Starter". Please bear in mind, you can only attempt one issue tagged as a GSoC Starter. Note also that we do not assign issues to people; we review the first pull request (PR) that solves an issue. Therefore, you can work on any issue you would like that does not already have an open/active PR against it. We also strongly suggest to work on a single issue/PR at a time. Once you have one PR merged, you are of course very welcome to tackle another issue, and so on. 

Could you please provide your GitHub handle? This is helpful for GSOC mentors to track which applicants are working on which issues. Since you are interested in Project 1, you may want to specifically check out related issues 1861 and 2188. Please note that we have a designated GSoC google group or #gsoc channel on our Discord server to discuss all things related to GSoC. 

We look forward to your contribution.

All the best,
Jenna

Project, Community and Outreach Manager

MDAnalysis * https://www.mdanalysis.org/

a fiscally sponsored project of NumFOCUS

[Oliver Beckstein]

Hi Christianna,

Welcome to MDAnalysis!

From your email I gather that you’re interested in GSoC with MDAnalysis. If this is the case, please introduce yourself also on the gs...@mdanalysis.org mailing list https://groups.google.com/a/mdanalysis.org/g/gsoc ! We keep the GSoC conversations on that list.

Best,

Oliver

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Oliver Beckstein (he/his/him)

email: orbe...@mdanalysis.org
twitter: @orbeckst

GitHub: @orbeckst

MDAnalysis – a NumFOCUS fiscally sponsored project

https://www.mdanalysis.org/