IFISC offers a new PhD student position, within the CSIC Momentum program, on the development of software solutions for the management and analysis of transportation data.
IFISC’s strategic objective is the study, exploration and development of information processing in and by complex systems. This comprises connecting existing approaches in different fields, developing common frameworks and the synthesis of novel information processing concepts. Within this context, this position for a PhD student aims at developing software solutions for managing data coming from different transportation systems, their merging, and their analysis using state-of-the-art techniques. Thanks to the technological advances in the last years, all modern transportation systems are generating large volumes of real-time information about their dynamics. Yet, their complexity results in a compartmentalisation of the associated insights, limited reproducibility, and that real implementations are seldom achieved.
Given this state of affairs, we propose the development of an open-source software library. Among other functions, it will allow applying unified cleaning and pre-processing algorithms; executing advanced data analyses, inspired in statistical physics' principles, Machine and Deep Learning; and further perform such analyses on multiple transportation modes in an integrated fashion.
Your tasks will be:
What we offer:
Requirements:
Additional information about this position, and the global program, can be found at: https://momentum.csic.es
Detailed information about this position is available at page 28 of the following document: https://momentum.csic.es/wp-content/uploads/2024/08/AGO_CATALOGO_OPORTUNIDADES_MOMENTUM_ESP_web.pdf
Application submissions must be made through the Bolsa de Trabajo
system of CSIC. It is nevertheless extremely advisable to get in touch
the the PI beforehand, by email at mzanin@ifisc.uib-csic.es, for further
clarifications on the process.
CSIC is an equal opportunity institution. Applications to this position by female or minority group scientists are particularly encouraged.