PhD fellowship in Computational biology for Integrative Microbiome and Meta

at  KU SCIENCE FOOD og NEXS

Department of Food Science invites applicants for a PhD fellowship in Computational biology for food and health. The project is part of the research project First principal models, neural networks and functional graphical models for Defining metabolic capacity as a Tool for Personalized nutrition (FOODTOP) , which is financed by the Novonordisk foundation Data Science initiative.
Start date is (expected to be) 1 January 2025 or as soon as possible thereafter.

WHO ARE WE LOOKING FOR?

We are looking for candidates within the field(s) of computational biolgy, bioinformatics, statistics or similar. Applicants can have a background in data science, mathematics, bioinformatics etc. and preferably have knowledge on microbiome and metabolomics data tied to nutrition.

QUALIFICATIONS NEEDED FOR THE REGULAR PROGRAMME

To be eligible for the regular PhD programme, you must have completed a degree programme, equivalent to a Danish master’s degree (180 ECTS/3 FTE BSc + 120 ECTS/2 FTE MSc) related to the subject area of the project, e.g. Scientific Computing, Signal Processing, Applied Mathematics, or Machine Learning. For information of eligibility of completed programmes, see General assessments for specific countries and Assessment database .

WE ARE LOOKING FOR THE FOLLOWING QUALIFICATIONS:

• Professional qualifications relevant to the PhD project
• Relevant publications
• Relevant work experience
• Other relevant professional activities
• Curious mindset with a strong interest in scientific computing and mathematical modeling
• Good language skills

• Carry through an independent research project under supervision
• Complete PhD courses corresponding to approx. 30 ECTS / ½ FTE
• Participate in active research environments, including a stay at another research institution, preferably abroad
• Teaching and knowledge dissemination activities
• Write scientific papers aimed at high-impact journals
• Write and defend a PhD thesis on the basis of your projec