PhD position in Computational Biology related to Aquaculture Biotechnology

Updated: about 2 months ago
Job Type: FullTime
Deadline: 23 Apr 2021

There is a vacancy for a PhD position in Computational Biology/Systems biology in the field of Aquaculture Biotechnology/Microbial ecology at the Department of Biological Sciences. The position is for a fixed-term period of 3 years with the possibility of a 4th year with compulsory other work (e.g. teaching duties at the Department). The position is fincanced by the University of Bergen and is connected to the Computational Biological Unit (CBU).

About the project/work tasks

The PhD project will be part of an international research project: ‘A microbial toolbox for RAS production and innovation (RASTOOLS)’. The project combines basic and applied research with the ultimate goal of reaching a better understanding of the connections between biological and chemical processes in recirculating aquaculture systems (RAS). RAS is a growing industry in Norway and globally. However, in order to reach a sustainable RAS industry in the future, we need a more holistic understanding of how various chemical and biological processes in these systems are connected. In particular, it is important to understand which measures should be taken to maintain a well functioning microbial biofilter and a high water quality in RAS. 

The PhD student will be involved in developing and analyzing mathematical models of the chemical and biological dynamics in RAS and to evaluate these models through controlled experiments in small scale pilot-RAS systems and through biological and chemical monitoring of large scale industrial RAS systems.

The student will be part of an international multidisciplinary research collaboration.

Working tasks:

  • Build and analyze mathematical models centered around connecting parameters such as supply of organics (fish food), fish metabolic activity (e.g. O2 consumption; CO2 and NH4+ production), microbial activity (e.g. consumption of CO2, NH4+ and organics), pH and alkalinity, oxygen supply, etc.
  • Bioinformatics analysis of metatranscriptomes and metagenomes from microbial biofilters. 
  • Statistical analysis of how environmental parameters control microbial diversity and activity. 
  • Model evaluation and refinement based on chemical and biological data.

A detailed plan of the students working tasks will be made together with the student and will depend on the students qualifications. 


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