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. Application form: https://www.nanogune.eu/en/nanogune/join-us/open-position/417-post-doctoral-researcher-data-analysis-machine-learning-spectroscopic-data Deadline for applications is the 31st of May, 2024
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regulatory matters is a great advantage for the position. Important tasks of the work plan • Development of machine learning models for the classification of in vivo Raman spectra, applying chemometric methods
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to extend the contract as part of other grants within the lab. The requirements for the position are: PhD degree in an area pertinent to the project, such as applied mathematics, statistics, machine learning
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implementation of algorithms and/or computational pipelines Background/experience in building statistical and/or machine learning methods, in particular for data integration tasks, would be a plus Previous
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months of fieldwork in the Bolivian Amazon and to travel for academic conferences. Ability and commitment to work both independently and collaboratively as part of a research team. Commitment to learning
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work with Prof. M. Ángeles Serrano and Prof. Marián Boguñá at the interface between Network Science and Machine Learning. The goal is to merge the best of the two worlds to produce a new generation of
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to machine learning models • Simulations and modification of data • Carrying out Raman measurements in vitro and in vivo • Development of protocols for biocompatibility and strict compliance with regulations
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science, machine learning and deep learning to various different data modalities. An ambition of this team is to implement predictive modelling as well as explainable AI methods to understand disease
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cutting-edge machine learning techniques to air quality data from a user-centered perspective Communicate scientific results within the Department, in international conferences and write quality papers in
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and renewable energy Artificial intelligence applied to social sciences - International Economy Artificial Intelligence and Machine Learning Work on High Frequency circuits, High Frequency Sensors