New PhD grant soon available

04/05/2018. PhD grant linked to project SynBioControl will be soon available. Computational metabolic network analysis for synthetic biology


Topic: Computational metabolic network analysis for synthetic biology


This position will be funded by the project  SynBioControl: Design, characterization and optimal tuning of synthetic biocircuits for bioproduction with control of the metabolic load  (MINECO/AEI/FEDER,UE  Grant DPI2017-82896-C2-1-R)




The project SynBioControl has been granted by the MINECO/AEI/FEDER,UE  (Grant DPI2017-82896-C2-1-R). New The biotech industry of the immediate future will integrate complex synthetic genetic circuits into microorganisms used as cell factories to produce proteins and metabolites of industrial importance. To this end, it has to deal with several critical problems that currently limit the applicability of synthetic biology: the rational design of synthetic genetic circuits of increasing complexity, their experimental characterization and robust tuning, and their industrial scaling. One of the main factors hindering the solution of these problems is the modification of the expected behavior of the circuits designed as a consequence of metabolic and genetic load of the cell caused by usage of shared time-varying cellular resources. Managing these phenomena requires the redesign of the circuits and the addition of additional feedback control mechanisms in order to maintain the specified design behavior. In this line SynBioControl adopts synthetic biology as a discipline of engineering, and emphasizes the application of engineering principles and methodologies via strategies of feedback control, computational optimization and multivariate analysis.The project focuses on a practical challenge and two related general objectives:

- General Practical Challenge: Design and implementation of feedback control mechanisms of protein and metabolite expression with consideration of the effects of metabolic and genetic load.

- Methodological Objective 1: Development of methods of structural design, analysis and robust parametric tuning of synthetic control genetic circuits through multiobjective optimization.

- Methodological Objective 2: Development of data analytics methods and grey models with application to scaling-up from the laboratory to the pre-industrial bioreactor.

To achieve these goals we will make use of methods from the areas of applied mathematics, optimization, systems engineering and control, and multivariate statistics.




This position deals with research in methods to link cell environmental conditions, metabolism, and  synthetic gene circuits. 


The candidate is expected to interact in a multidisciplinary team, comprising the SB2C Lab (Synthetic Biology and BioSystems Control Lab) and GIEM group (research group in multivariate statistical engineering) at the Technical University of Valencia, and the (Bio)process Engineering Group at IIM-CSIC. The candidate will be anchored at the SB2C Lab (Valencia, Spain) with Prof. Jesús Picó and Prof. Alberto Ferrer as supervisors. 


The ideal candidate should have a degree in engineering, applied maths, biophysics, physics or equivalent discipline, and have some proficiency in programming languages (e.g. Matlab, Maple).  Notice some background in biology, or the willingness to learn cell biology, and even basic biology laboratory skills, will be a requisite. 




  • Gross salary around 1200€/month, 12+2 months/year.

  • There is also the option to obtain funding for conferences and on leave stays.

  • Duration of the contract: 4 years.




Please send a letter in English, including a personal motivation, your academic grades (including ranked position in the student cohort) and curriculum vitae, to Jesús Picó ( and Alberto Ferrer (