Sort by
Refine Your Search
-
14 Jul 2026 Job Information Organisation/Company FAPESP - São Paulo Research Foundation Research Field Computer science Researcher Profile Established Researcher (R3) Application Deadline 9 Aug 2026 - 23:59 (UTC) Country Brazil Type of Contract To be defined Job Status Not Applicable Is the job...
-
to industry and developments with Deep Learning (DL), Computer Vision (CV), Transformers, Large Language Models (LLMs), Natural Language Processing (NLP). Mandatory requirements • Bachelor's degree
-
data and deep learning methods to assess canopy cover, quality, carbon stocks, and ecosystem services. Mandatory requirements: PhD in areas related to forest resources, remote sensing, data science, or
-
, and machine learning; and the development of ecological indicators for environmental monitoring in the Campos and Santos Basins, Brazil. Mandatory requirements Applications from people with training in
-
machine learning algorithms to support the traceability of the beef’s geographical origin. She/he will participate in all stages of the project, including planning and supervision of sample collection and
-
-doctoral fellowship in person in São Paulo, Brazil. Fluency in English. Basic knowledge of statistics and willingness to learn how to conduct systematic reviews and meta-analyses. Previous experience in
-
networks, from a machine learning and information theory perspective. This basic research project has strong translational potential and aims to elucidate how immune function is altered during sepsis, with
-
position within a Research Infrastructure? No Offer Description Activities and context: The fellow will develop machine-learning interatomic potentials (MLPs), trained on density functional theory-DFT data
-
chromatography. The candidate will prepare samples for immunopeptidomics by liquid chromatography coupled with mass spectrometry tandem (LC-MS/MS), analyze large datasets, and develop scripts and machine learning
-
; • Familiarity with statistical analyses and modeling as well as machine learning approaches, supported with strong skills in computational optimization of methods; • Experience working with large-scale datasets