-
techniques for environmental sciences – information provided in the CV and/or motivation letter; e) Experience in statistical analysis, preferably in an R environment – information provided in the CV and/or
-
December and updated by Decree-Law nr 108/2023, from 22nd of November. International environment and experience: Diversity is a fundamental aspect of the essence of iMM, where researchers and non
-
for admission: MSc degree in Meteorology, Oceanography and Geophysics (MOG) or in Engineering of Energy and Environment (EEA) and proven experience in meteorological fire danger. 3. Additional
-
28 Mar 2024 Job Information Organisation/Company FCiências.ID Department HR Research Field Biological sciences Environmental science » Ecology Computer science » Modelling tools Researcher Profile First Stage Researcher (R1) Country Portugal Application Deadline 29 Apr 2024 - 23:59...
-
CIIMAR - Interdisciplinary Center of Marine and Environmental Research - Uporto | Portugal | about 1 month ago
and highly multidisciplinary environment with a strong connection to the Ocean. Duration of the contract: An uncertain term work contract will be signed starting April 2024, under the regime
-
CIIMAR - Interdisciplinary Center of Marine and Environmental Research - Uporto | Portugal | about 1 month ago
the modern Cruise Ship Terminal of the Port of Leixões, in Matosinhos, Porto’s metropolitan area. The selected candidate will work in an international and highly multidisciplinary environment with a strong
-
physiological, biochemical and molecular techniques to respond to relevant challenges related to the study of the microbiome (soil and plant) and its relationships with the environment and with the agronomic
-
CIIMAR - Interdisciplinary Center of Marine and Environmental Research - Uporto | Portugal | 3 months ago
of CIIMAR, in the modern Cruise Ship Terminal of the Port of Leixões, in Matosinhos, Porto’s metropolitan area. The selected candidate will work in an international and highly multidisciplinary environment
-
deploy Multi-Agent Reinforcement Learning (MARL) models based on TD-Learning and/or Q-Learning, as well as corresponding environments and tasks. • Explore MARL models and environments at different degrees
-
the motivation letter; c) Experience in managing big datasets - information provided in the CV and/or in the motivation letter; d) Knowledge in scripting environments (Linux, Unix, Mac), programming languages like