collection flaws, to instrumental failures or the presence of unwanted physiological responses. Something as apparently simple as the optimal coupling between the experiment design and the subsequent analysis pipeline, which are known from basic mathematical principles to be tightly coupled, defies regular practice. In other words, best practices and standards are insufficient to optimize scientific practice in fNIRS or afford automation of science; a paradigm which is already achievable in other branches of science [3]. Underpinning such feat is an ontology of experimental design and analysis.

This project intends to advance OntoNIRS [4] from its current embryonic state into a fully operational ontology capable of supporting reasoning regarding experimental designs and analysis for fNIRS neuroimaging. In order to do so, the different stages of ontology engineering processes should be completed and the outcome verified and validated against existing literature as well as formal methods. To realize these goals, contributions in computational neuroimaging, knowledge representation (inc ontologies and logic) and natural language processing are needed in a truly multidisciplinary project requiring knowledge from fields as diverse as optics, mathematics, neurosciences, and computer sciences.

Applicants should have a strong background in mathematics and physics, and being enthusiastic about computer sciences. You should have a commitment to research in mathematical modelling and computer simulations and acquiring fNIRS neuroimaging data with applications in neuroscience. You must have exceptional programming and communication skills. You will be a team-player capable of independent learning.

Expected starting date: September 2025

collection flaws, to instrumental failures or the presence of unwanted physiological responses. Something as apparently simple as the optimal coupling between the experiment design and the subsequent analysis pipeline, which are known from basic mathematical principles to be tightly coupled, defies regular practice. In other words, best practices and standards are insufficient to optimize scientific practice in fNIRS or afford automation of science; a paradigm which is already achievable in other branches of science [3]. Underpinning such feat is an ontology of experimental design and analysis.

This project intends to advance OntoNIRS [4] from its current embryonic state into a fully operational ontology capable of supporting reasoning regarding experimental designs and analysis for fNIRS neuroimaging. In order to do so, the different stages of ontology engineering processes should be completed and the outcome verified and validated against existing literature as well as formal methods. To realize these goals, contributions in computational neuroimaging, knowledge representation (inc ontologies and logic) and natural language processing are needed in a truly multidisciplinary project requiring knowledge from fields as diverse as optics, mathematics, neurosciences, and computer sciences.

Applicants should have a strong background in mathematics and physics, and being enthusiastic about computer sciences. You should have a commitment to research in mathematical modelling and computer simulations and acquiring fNIRS neuroimaging data with applications in neuroscience. You must have exceptional programming and communication skills. You will be a team-player capable of independent learning.

Expected starting date: September 2025