We have opened a research engineer position related to a couple of collaborative projects in which Datlas is engaged, starting in the fall of 2023 (in numerical oceanography and remote-sensing ocean data inversion, see details below).
Contact us to apply (or click here (in french)).
Based in Saint-Martin d’Hères (38), on the university campus, DATLAS (https://www.datlas.fr/) is a cooperative of entrepreneur-researchers and -engineers working together to take up scientific and numerical challenges in environmental and climate sciences to better address societal issues.
DATLAS is a private company, created as a branch of OXALIS, a cooperative of activity and employment that provides an economic, legal, social and human framework supporting the development of DATLAS activities.
The DATLAS team currently has 7 members, with expertise in numerical methods and numerical models applied to Earth data, ranging from observations to model simulations. Our on-going activities are related to spatial observations, modeling and forecasting of the ocean and of sea ice:
Datlas is involved in activities to design and process future and present space observation missions, building on high-quality and high-resolution numerical simulations of the ocean, and on the development of innovative numerical methods and models. Datlas is also involved in activities to develop and improve numerical models of the ocean and sea ice in order to better understand existing observations and the physical processes at play, and to better forecast the physical properties that matter for operational stakeholders and end-users.
Two new collaborative projects are starting in 2023, for which DATLAS is opening a position to be filled as soon as possible, in the form of a fixed-term contract for 12 months:
The World Ocean Circulation (WOC) project, funded by the European Space Agency (ESA) : this is an extension of a 24-month project, which aims to deliver demonstrator algorithms for surface current reconstruction, based on available remote-sensing and in-situ observations. More specifically, the role of Datlas in this project is to estimate the inertial component of the surface current with learning methods on drifting buoy and surface wind data. An algorithm has already been prototyped over the last two years, and will need to be tested and validated on a global scale.
The ODYSEA project, funded by the French National Centre for Space Studies (CNES): This CNES/NASA mission project aims at observing surface wind at the synoptic scale, and also of ocean surface current, which constitutes one of the last fundamental variables of the ocean surface dynamics that is not directly observed from satellite to date. In this project, the role of Datlas is to explore new methods of mapping of the total current (including inertial, but also geostrophy components) on the basis of highly-resolved data (from numerical simulations) and fundamental dynamical laws.
The nature and the proposed missions are detailed below, and will be refined depending on the candidate.
Mission 1 :Get started with the prototyped algorithm (written in Python) for the inertial current in its North Atlantic configuration. Get started with the datasets used (in situ and spatial data), and with the validation metrics. During this first stage, beyond the algorithmic, a critical mind on the validation of the data would be appreciated.
Mission 2 :Rescale the algorithm for a global application, which will require a revisit of the parallelization architecture and a better optimization of the reading and processing steps of the input data
Mission 3 : Based on the developed algorithm, produce a 10-year time series of surface currents, and perform its validation based on independent data. Communication to the other project partners and to ESA will be required (participation in conferences with oral presentations in English).
Masters degree (of higher) in applied mathematics and/or Earth sciences. Some experience in signal processing and scientific computing is required. Skills in Python programming with parallelization tools is recommended. An interest in geophysical fluid modeling and data inversion would be highly appreciated. Autonomy and scientific curiosity. English written and spoken.