The European Organisation for Astronomical Research in the Southern Hemisphere (ESO) is the foremost intergovernmental astronomy organisation in Europe and the world’s most productive ground-based astronomical observatory. ESO carries out an ambitious programme focused on the design, construction and operation of powerful ground-based observing facilities enabling astronomers to make important scientific discoveries.
For its Data Management and Operations (DMO) Division within the Directorate of Operations at its Headquarters in Garching, near Munich, Germany, ESO is advertising the position of Data Scientist (Deep Learning).
The key goal of the Data Scientist will be to develop and apply innovative Deep Learning techniques to object classification in ESO and ALMA Science Archives (http://archive.eso.org/cms.html and https://almascience.eso.org/alma-data/archive, respectively). With a user base of thousands of scientists, they are a rich and powerful resource for the astronomical community worldwide.
Main Duties and Responsibilities:
The Data Scientist postholder will be responsible for designing, building and training a system based on Deep Learning object classification techniques with the goal to automatically classify astronomical images and spectra to open-up innovative ways for scientists to use the data.
The postholder will research the algorithms most suitable for the content of ESO’s Science Archives. They will be expected to contribute innovative ideas to develop the system and critically evaluate and verify the results, including an analysis of limitations. The application of the developed methodologies to data beyond ESO’s current concepts may also be explored.
Prototyping in suitable programming and/or scripting languages will be part of the Data Scientist’s duties. They will frequently interact with internal and external colleagues to present and discuss results achieved and to plan the next steps ahead.
The position is in the context of the EU project 824064 – The European Science Cluster of Astronomy & Particle Physics ESFRI Research Infrastructures (ESCAPE). This project addresses the critical questions of open science and long‐term reuse of data by joining many of the largest European scientific facilities in physics and astronomy.
For more details on the position and instructions on how to apply, please visit: http://jobs.eso.org/
Deadline for application is 25 January 2019