Research Fellow, Experimental Evolutionary Ecology and Omics

Job Purpose

One 30-month postdoctoral research fellowship in Experimental Evolutionary Ecology and Omics is available within the School of Biosciences in the Environmental Genomics Group at the University of Birmingham, UK.

"Cracking the Code of Adaptive Evolution” (dCODE) is a multidisciplinary collaboration among seven investigators at the University of Birmingham who form a vibrant research community to advance the field of environmental omics. We pursue foundational science using natural populations of the ecologically relevant model species Daphnia. This project seeks to discover the relative contributions of phenotypic plasticity, the epigenome, and of molecular evolution to the process of adaptation, by experimenting on an historical Daphnia population that is “resurrected” from dormancy spanning 100 years of evolution.

The candidate will contribute to the planned research by (1) designing and conducting experiments to assess fitness changes leading to species persistence in presence of anthropogenic stress; (2) performing advanced statistical analyses to summarize fitness responses at species level; (3) linking fitness responses at species level with ecosystem services. Ability to code in R or similar software is required. The ideal candidate will: (i) understand theoretical underpinnings of evolutionary theories; (ii) have proven experience in conducting and analyzing experiments in the field of evolutionary ecology; (iii) have prior knowledge on how to link biodiversity and genetic diversity to ecosystem functioning and services; (iv) have prior experience with working in a multidisciplinary context.

The successful candidate will be responsible for all aspects related to laboratory experiments using Daphnia.

Applicants must hold a PhD-degree with substantial experience in experimental evolution design and analysis, statistics and biostatistics. Ability to perform ecological modeling and in combining experimental and omics data will be considered an advantage.

Person Specification

• First degree in area of specialism and normally, a higher degree relevant to research area or equivalent qualifications with substantial experience in experimental evolution design and analysis, statistics and biostatistics.
• High level analytical capability
• Ability to communicate complex information clearly
• Fluency in relevant models, techniques or methods and ability to contribute to developing new ones
• Ability to assess resource requirements and use resources effectively
• Understanding of and ability to contribute to broader management/administration processes