(Português do Brasil) Oportunidade Doutorado Hungria – Prof. József Baranyi

07/10/2019 10:23

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Interconnected World – Interacting Sciences

Combine your computational and numerical skills with life sciences!

Embed your home culture in its European roots and enrich both!

That is:  BUILD BRIDGES!  Go for an interdisciplinary PhD at a special place!

– O que: Apresentação de oportunidade de Doutorado na Hungria na Universidade de Debrecen – http://edu.unideb.hu 

– OndeAuditório 1 do EQA
– QuandoQuarta-feira, 09 de outubro/2019 – 17:30 h
 Quinta-feira, 10 de outubro/2019 – 14:00 h
– ApresentadorProf. József Baranyi, pesquisador líder dos projetos e orientador 
– Temas de tese:  “new, truly interdisciplinary areas, Predictive Food Microbiology and Computational Nutrition

– Requisitos1) possesses (or develop, by the start of the project) a good standard of English; 2) Habilidades em ciências exatas (tais como: Modelling; e/ou Numerical mathematics; e/ou Parametric statistics; e/ou Optimization; e/ou Big data and its computational tools; e/ou Network science; e/ou Programming).

Dr József Baranyi
Nas datas acima, o Prof. József Baranyi estará pessoalmente para explicar os temas, o financiamento do projeto, a oportunidade de bolsas e outras dúvidas que surgirem.
Ainda, aqueles que não puderem comparecer podem escrever e tirar dúvidas: jozsef.baranyi@gmail.com (Prof. Baranyi) ou bruno.carciofi@ufsc.br (Prof. Bruno, UFSC). Porém, aqueles que tiverem contato direto no Prof. Baranyi terão vantagens no processo de seleção.

Project 1.

Bacterial kinetics in food are determined by the temperature and the food environment, primarily the pH and water availability. The effect of these factors on the population’s maximum specific growth rate, its most important parameter, is commonly described by multivariate functions, that can be approximated by response surfaces over data available from such datasets as ComBase (www.combase.cc). The best structure of such empirical response surfaces is still not clarified. In this project a comprehensive numerical analysis will be carried out to answer the question, with special emphasis on the interaction between the parameters of those response surfaces, such as the cardinal values of the environmental factors, i.e. the minimum, maximum and optimum values in their growth regions.

This research will be conducted in close collaboration with Nestlé Research Center, Lausanne, Switzerland.

The ideal PhD candidate is an MSc in applied mathematics, physics, engineering, with a strong affinity to food/health-related life sciences or vice versa. To be able to work effectively with international collaborators, it is vital that that candidate possesses (or develop, by the start of the project) a good standard of English.

 

Project 2. “Big Data” and computational nutrition for healthy diet

Health and nutrition are primarily linked in the context of the human genome and microbiome. The genome is a set of genes defining the immune system and the internal environment in the GIT (Gastro-Intestinal Track) where the microbes help to break down the food that we eat.

Both genome and microbiome have been increasingly researched by computational methods, data mining and bioinformatics. The key here is the recognition that, with the advent of “big data” (the explosion of observations stored electronically), new patterns emerge, challenging many previously rock-solid dogmas. These patterns can only be detected by advanced computational and statistical tools and this project is an example for the interdisciplinary science of computational nutrition.

A database will be built to find patterns between constantly evolving diets and the big three diseases characteristic of later life: cancer, cardiovascular diseases and dementia. Data from publications as well as internet databases will be browsed by a specifically created data-mining software tool (a “crawler”), and the results will be analysed and visualized by network science and statistical methods. The research will contribute to a related big programme, Foodome, (https://www.barabasilab.com/projects), of the world-renowned Barabási Lab, and will be carried out in collaboration with partners from medical and food sciences.

The ideal PhD candidate is an MSc in informatics with strong affinity to food/health-related life sciences or vice versa. To be able to work effectively with international collaborators, it is vital that that candidate possesses (or develop, by the start of the project) a good standard of English.