Carlos Cabral
Angestellt, Data Strategist, Novartis Oncology
Deutschland
Werdegang
Berufserfahrung von Carlos Cabral
Bis heute 3 Jahre, seit Juni 2021
Data Strategist
Novartis Oncology
1 Jahr und 9 Monate, Okt. 2016 - Juni 2018
Medical Data Scientist
arvato health analytics GmbH
Development and implementation of machine learning methods for biomarker development Translation of mathematical models to a biological framework . Management, organisation and processing of human data (neuroimaging, clinical, neuropsychological and genetic data) . IT systems design, implementation and management. Supervision of junior researchers . Technical and methodological coordination of the EU-FP7 project PRONIA . Teaching of Multivariate Pattern Analysis Methods to Lab and PRONIA members.
1 Jahr und 7 Monate, März 2012 - Sep. 2013
Junior Researcher
Institute for Systems and Robotics
Development and implementation of machine learning tools to analyze data from the Alzheimer’s Disease Neuroimaging Initiative Analysis and processing of Positron Emission Tomography and structural Magnetic Resonance Imaging volumes Translation of mathematical models to a biological framework
9 Monate, Juni 2011 - Feb. 2012
Junior Researcher
Institute for Systems and Robotics
Processing and univariate analysis of functional magnetic resonance volumes Development and implementation of machine learning methodologies to classify cognitive states using functional magnetic resonance volumes Interpretation of brain activity patterns and their relation with the decoded stimuli
Ausbildung von Carlos Cabral
2 Jahre und 3 Monate, Sep. 2008 - Nov. 2010
Biomedical engineering
Instituto Superior Técnico
Signal Processing, Data Analysis, Neuroimaging, Machine Learning
3 Jahre und 11 Monate, Sep. 2005 - Juli 2009
Biomedical engineering
Instituto Superior Técnico
Engineering, Programming, Medical Sciences, Algebra, Data modeling, Statistics, Calculus, Signal Processing, Chemistry, Biochemistry
Sprachen
Deutsch
Gut
Englisch
Fließend
Portugiesisch
Muttersprache
Spanisch
Grundlagen