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of the following methodologies: optogenetics, calcium imaging, viral tracing, tissue clearing, murine behavioral phenotyping, machine-learning behavioral analysis Familiarity with programming languages
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computer software; Assisting with preparing grant applications to secure further funding for relevant projects; Helping establish new projects and research consortia relating to the Zuccolo Group research
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biophysics, computational biology, mathematics in the life sciences, computer science and machine learning with application to biological systems, and related areas. What we provide The CSBD provides fully
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at the intersection between analytical chemistry, chemometrics and life sciences. As a postdoc in this project you will learn to use and help to develop cutting-edge methodologies linked to vibrational spectroscopy and
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the beginning and there is still much to be learned! You will lead a project that centers on how tactile end organs assemble, function, and recover after injury. You will be using non-standard animal models
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applications, for example in machine learning and mathematical statistics Participation in the scientific activities of the department, e.g. seminars, workshops and schools organised by the members
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will develop atomistic models and machine-learning potentials to interpret experimental data and predict catalytic performance. The tasks can include Advancing equivariant neural network potentials
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analysis to translate THz signals into optical material properties such as refractive index and absorption coefficient. Development of machine learning algorithms for material classification. Exploration
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) training personalized computational models in new contexts, and (iii) studying in-silico clinical intervention strategies. The postdoctoral fellow will have the opportunity to: Learn about computational
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constitutive androstane receptor (CAR) as models. PXR and CAR transcriptionally regulate cytochrome P450 3A4 (CYP3A4) and CYP3A5-drug-metabolizing enzymes that metabolize more than 50% of clinical drugs