adavaria

.gitignore

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 .idea*
+adavaria/mlband/__pycache__*
+adavaria/data*
+**/*.pyc
+adavaria/results/*
+adavaria/build/*
+adavaria/mlband.egg-info/*
+adavaria/dist/*
+.DS_Store
+

adavaria/ML-Band-Gaps.md

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+# ML Band Gaps (Materials)
+
+> Ideal candidate: skilled ML data scientist with solid knowledge of materials science.
+
+# Overview
+
+The aim of this task is to create a python package that implements automatic prediction of electronic band gaps for a set of materials based on training data.
+
+# User story
+
+As a user of this software I can predict the value of an electronic band gap after passing training data and structural information about the target material.
+
+# Requirements
+
+- suggest the bandgap values for a set of materials designated by their crystallographic and stoichiometric properties
+- the code shall be written in a way that can facilitate easy addition of other characteristics extracted from simulations (forces, pressures, phonon frequencies etc)
+
+# Expectations
+
+- the code shall be able to suggest realistic values for slightly modified geometry sets - eg. trained on Si and Ge it should suggest the value of bandgap for Si49Ge51 to be between those of Si and Ge
+- modular and object-oriented implementation
+- commit early and often - at least once per 24 hours
+
+# Timeline
+
+We leave exact timing to the candidate. Must fit Within 5 days total.
+
+# Notes
+
+- use a designated github repository for version control
+- suggested source of training data: materialsproject.org