BALEARIC ISLANDS COASTAL OBSERVING AND FORECASTING SYSTEM (SOCIB)

The Coastal Observation and Prediction System of the Balearic Islands (SOCIB) is a state-owned
public consortium established under Spain’s Public Sector Legal Regime and has been
recognized as a Singular Scientific and Technical Infrastructure (ICTS) since 2014.
Located at Parc Bit in Palma, SOCIB boasts a multidisciplinary team dedicated to advancing
knowledge and fostering the sustainable management of the ocean. We operate a
comprehensive observation and prediction system in the Western Mediterranean, continuously
collecting data from the coast to the open sea using diverse platforms (including coastal radars,
beach monitoring systems, gliders, lagrangian platforms, fixed oceanographic buoys,
meteorological and sea-level stations, and oceanographic research vessel). Our prediction
system encompasses operational ocean, wave, and meteotsunami prediction models. All
meteo-oceanographic data are available in real-time and open access through the SOCIB
Meteo-Oceanographic Data Repository. Beyond data collection, SOCIB develops digital
applications for knowledge transfer and evidence-based marine management, offers advisory
services, and actively promotes Ocean Literacy.
SOCIB’s mission is to operate a cutting-edge observation and prediction system in the Western
Mediterranean, providing essential data, facilities, services, and digital tools to deepen our
understanding of the ocean and transfer this knowledge to society. Our vision is to be a leading
marine research infrastructure, contributing significantly to the development of a digital twin of
the Mediterranean to support climate change decision-making.

Homepage: https://www.socib.es/en

Reporting to the Head of the Scientific Area, the person holding the position of Head of the
Modeling and Forecasting Facility will contribute to the implementation of the “SOCIB 2030:
Western Mediterranean Digital Twin” roadmap. Main duties include:

• Optimization of operational modeling systems
  ○ Maintain and improve existing operational modeling systems (WMOP, BRIFS),
  based on ROMS and WRF.
  ○ Enhance data assimilation capabilities from satellite imagery, Argo profiles,
  gliders, HF radars, etc., in collaboration with the observation teams

• Ocean modeling research
  ○ Lead the development, implementation, and validation of cutting-edge numerical
  models and data assimilation techniques. This will potentially involve applying
  machine learning and AI to ocean data analysis and modeling, aiming to enhance
  ocean forecasts and SOCIB‘s research applications.
  ○ Lead research-oriented process studies to advance the understanding of physical
  and multidisciplinary ocean processes, in line with SOCIB‘s mission and vision.
  ○ Explore AI, machine learning, and high-performance computing algorithms for
  data analysis and to improve the performance and predictive capabilities of
  SOCIB‘s models

• Leadership, coordination and strategy of the Modeling and Forecasting Facility
  ○ Align the Modeling and Forecasting Facility with SOCIB’s scientific strategy
  Coordinate MFF activities with other SOCIB facilities and strengthen collaboration
  with research institutions and industry

• Team and project management of the Modeling and Forecasting Facility
  ○ Lead a multidisciplinary team including researchers, engineers, technicians, and
  students
  ○ Manage project proposals and lead national and international R&D projects to
  successful completion

• Scientific publication and dissemination
  ○ Publish in high-impact journals, present at conferences, and engage in outreach
  activities.

To participate in this call, all interested individuals who meet the minimum requirements outlined
in the specific terms must submit their application and required documentation by email to:
rrhh@socib.es.
Please ensure the call’s reference is clearly indicated in the email subject line.
Mandatory documentation for each phase is detailed in the specific terms for the position.
The application email, CV, descriptive report of professional experience and career, copy of an
identification document (DNI, NIE, passport, or equivalent), and supporting documentation for
minimum requirements must all be submitted before the deadline specified in the specific terms.
Failure to provide the aforementioned documentation will result in the candidate’s exclusion,
though rectification of defects will be permitted within the established timeframe.
Participation in this selection process implies full acceptance of the terms of the call. The
Selection Committee reserves the right to declare the position vacant if no suitable candidate is
found.
The candidate’s email address will be considered a valid means for all requests and notifications.