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The Swiss Data Science Center was founded through a strategic focus area of the ETH Board and has offices at EPFL, ETH Zurich and the Paul Scherrer Institute (PSI). Our mission is to help academic teams and industries leverage data science and state-of-the-art machine learning. In other words, SDSC aims at bridging the gap between those who create data, those who develop data analytics and systems, and those who could potentially extract value from it. The centre is composed of a large and diverse multi-disciplinary team.

For more details on our academic research collaborations see here.

We are currently looking for a Senior Data Scientist.

We are looking for a Senior Data Scientist with experience in working with large geolocated environmental datasets from multiple sources, either from gridded data such as Earth observation data or climate models, or ground-level measurements such as field sampling, automated weather stations, punctual measurements, etc.

Your practical machine-learning knowledge will help domain experts working in Earth and environmental sciences, physics, and biology to identify the best ways to analyse and model their data, develop suitable algorithms and answer complex scientific questions.

The position requires the candidate to actively and regularly engage with domain experts from research groups of the ETH Domain (EPFL, ETH Zurich, EMPA, EAWAG, PSI, and WLS); either in the framework of an established collaboration between SDSC and the Swiss Polar Institute or within the Speed2Zero Joint Initiative, aiming at using modern machine learning and data science for the climate sciences.

Your work includes, but is not limited to, determining which machine learning approaches and formulations are most effective, developing models, algorithms, implementations and performing the evaluations hand-in-hand with the domain scientists.

We expect the ideal candidate to be able to perform research independently, and to have excellent communication skills.

A track record of successful research projects, with corresponding scientific publications and open-source code, is a plus. 

Your profile: 

- You are a researcher with a Ph.D. in machine learning or a related field, with experience in multidisciplinary research with sharp skills in one or more of the following fields:

• Deep Learning
• Bayesian Modelling
• Computer Vision
• Statistics
• Optimisation
• Signal Processing

- You can work with complex datasets and can develop appropriate machine learning models for challenging real-world problems

- You can handle diverse data sources and exploit them jointly to tackle specific research and practical questions

- You are proficient in one or more among Python, Julia, R, Scala, and C/C++ and familiar with databases, version control and Jupyter ecosystem. 

- You are familiar with open science and open research data principles, and familiar with the issue of reproducibility in scientific experiments. - Experience in releasing open-source code and data is also expected.

We offer :

• A stimulating, cross-disciplinary environment
• Opportunities for turning research into impactful solutions
• Excellent ties to research groups worldwide

We look forward to receiving your online application with the following documents:

• Letter of motivation
• CV
• Google Scholar profile

Please note that we exclusively accept applications submitted through our online application portal. Applications via email or postal services will not be considered.

Further information about the Swiss Data Science Center can be found on our website. Questions regarding the position should be directed to Fernando Perez-Cruz, by email at Write an email or Michele Volpi, by email at Write an email (no applications).

For recruitment services the GTC of ETH Zurich apply.