Pilar Navarro Ramírez
AI Research Scientist at Panacea Cooperative Research- Claim this Profile
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Inglés Full professional proficiency
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Alemán Elementary proficiency
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Español Native or bilingual proficiency
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Francés Limited working proficiency
Topline Score
Bio
Credentials
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Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization
deeplearning.aiSep, 2020- Nov, 2024 -
Interactivity with JavaScript
University of MichiganSep, 2020- Nov, 2024 -
Structuring Machine Learning Projects
deeplearning.aiSep, 2020- Nov, 2024 -
Introduction to CSS3
University of MichiganAug, 2020- Nov, 2024 -
Introduction to HTML5
University of MichiganAug, 2020- Nov, 2024 -
Neural Networks and Deep Learning
deeplearning.aiAug, 2020- Nov, 2024
Experience
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Panacea Cooperative Research
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Spain
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Research Services
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1 - 100 Employee
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AI Research Scientist
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Dec 2022 - Present
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Wildlife.ai
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New Zealand
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Environmental Services
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1 - 100 Employee
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Volunteer
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Nov 2022 - Present
Collaboration as a computer scientist in the development of the Koster Seafloor Observatory project. Collaboration as a computer scientist in the development of the Koster Seafloor Observatory project.
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Universidad de Granada
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Spain
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Higher Education
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700 & Above Employee
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Beca de colaboración en el Departamento de Ciencias de la Computación e Inteligencia Artificial
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Nov 2021 - Sep 2022
Development of a deep learning-based software for fully automatic segmentation of prostate cancer lesions, both clinically significant and not clinically significant, in prostate T2-weighted MRI. Various real clinical MRI images publicly available together with their associated ground truth segmentation masks were used to train, calibrate and evaluate deep learning models for the task of segmenting the prostate zones and prostate tumors. Development of a deep learning-based software for fully automatic segmentation of prostate cancer lesions, both clinically significant and not clinically significant, in prostate T2-weighted MRI. Various real clinical MRI images publicly available together with their associated ground truth segmentation masks were used to train, calibrate and evaluate deep learning models for the task of segmenting the prostate zones and prostate tumors.
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Education
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Universidad de Granada
Bachelor's degree in Computer Engineering, 8.5 -
Master D
Curso superior de zoología -
Universidad de Granada
Bachelor's degree in Mathematics, 8.15 -
University of Duisburg-Essen
Computer Science, 8.8