pat-s
Patrick Schratz
Zurich, Switzerland

I am a PhD student within the GIScience group at the Department of Geography. I focus on the application of statistical- and machine learning techniques to address research questions related to environmental issues. Beside the scientific part I am also interested in the development of (geo)statistical programming solutions to simplify todays data science challenges. Check the projects section for detailed information. I like to write about the Linux world, R stuff and other technical topics that I find interesting.

CodersRank Score

What is this?

This represents your current experience. It calculates by analyzing your connected repositories. By measuring your skills by your code, we are creating the ranking, so you can know how good are you comparing to another developers and what you have to improve to be better

Information on how to increase score and ranking details you can find in this blog post.

3,065.7
CodersRank Rank
Top 1%
Based on:
Stackoverflow 114 events
Top 50
CSS
CSS
Developer
Switzerland
Top 5
R
R
Developer
Switzerland
Highest experience points: 0 points,

0 activities in the last year

List your work history, including any contracts or internships
cynkra GmbH
Jun 2020 - Jul 2020 (1 month)
Zürich, Schweiz
Data Scientist
r git
Friedrich-Schiller-Universität Jena
4 years 6 months
Jena, Germany
Researcher
May 2019 - Jun 2020 (1 year 1 month)
Researcher
Oct 2016 - Apr 2019 (2 years 6 months)
Project: EU LIFE Healthy Forest
Research Assistant
Apr 2015 - Mar 2016 (11 months)
Project: Forest-DRAGON 3
LMU - Ludwig-Maximilians-Universität München
May 2019 - Jun 2020 (1 year 1 month)
Remote
Research Engineer

Add some compelling projects here to demonstrate your experience
EU LIFE Environment and Resource Efficiency project „Healthy Forest”
Apr 2016 - Present
The EU LIFE Environment and Resource Efficiency project „Healthy Forest” aims to design and apply advanced methodologies to achieve a more sustainable forest management in the field of control and prevention of forest decline caused by invasive and pathogenic agents. An important step toward this objective is the development of an early detection system and monitoring of forest health in the field, in the laboratory and by remote sensing. The sub-project conducted by the Geographic Information Science (GIScience) group at the Department of Geography of the University of Jena focuses on spatial modeling of forest disease potential at the regional scale, and on the application of computational and statistical techniques to identify significant predictors of forest decline in high-dimensional hyperspectral remote-sensing data.
ESA Forest-DRAGON 3
Oct 2014 - Jul 2016
Dragon 3 focuses on exploitation of ESA, TPM and Chinese EO data for geo-science and applications development in land, ocean and atmospheric applications. The Programme brings together joint Sino-European teams to investigate 50 thematic projects
This section lets you add any degrees or diplomas you have earned.
Bachelor of Science (B.Sc.), Geography
Dec 2010 - Dec 2013
Specialisation: GIS & Remote Sensing

Thesis: "Investigation of the ASAR BIOMASAR GSV
maps from 2005 and 2010 using optical satellite data at
different temporal and spatial resolution in Northeast
China” (in the framework of ESA Forest-DRAGON 3)
Friedrich-Schiller-Universität Jena
Master of Science (M.Sc.), Geoinformatics & Remote Sensing
Dec 2013 - Dec 2015
Thesis: "Modeling the Spatial Distribution of Hail Damage in Pine
Plantations of Northern Spain as a Major Risk Factor for
Forest Disease"
Reporting with R Markdown
Python Step by Step: Build a Data Analysis Program
Intro to Statistics with R: Introduction

Jobs for you

Show all jobs
Feedback