The EEOB Department at ISU offers a great environment for postdoctoral scholars. The departmental culture is collaborative and interactive with many opportunities for postdocs to participate in activities that contribute to your training as a future PI. I am interested in collaborating with postdocs with any research background––including those from biology, computer science, or statistics. Moreover, I am happy to discuss research projects spanning the spectrum between purely theoretical/computational work to entirely empirical.
As a postdoctoral researcher, you should take this time to develop your own, independent research program. Consider the skills you wish to develop during this time and how the training will help you attain a permanent position in whatever sector you aspire to (e.g., tenure track, government, industry, teaching, etc.). Additionally, think about your unique skills and how your contributions will be "value added" to my lab and EEOB.
Overall, I am looking for postdocs who will actively participate in the academic community. I will treat you like an independent colleague and work to provide you with the training and opportunities you need to further your career. I was very fortunate during my time as a postdoc to be treated this way and I fully intend to pay it forward.
I am excited to work with anyone interested in phylogenetics and evolutionary biology. Otherwise, there are no limits to the types of postdoctoral projects I would support in my research group. For empiricists, there is no requirement for you to write software or develop statistical models and if you pursue research in my lab, we can think of lots of cool ways to combine our skills.If you have a computational biology background, there will be several opportunities for you to become involved in my ongoing software projects (though absolutely not required). In particular, I am on the development team of the program RevBayes and we are always happy to take on new developers and collaborators.
The successful applicant will collaborate with us on a new, NSF supported project using sequence capture and GBS data to investigate the coevolutionary history of species interactions in Central American figs and their pollinating (mutualistic) and non-pollinating (antagonistic) fig wasps. Collaborators on the project include Drs. John Nason and Tracy Heath (Iowa State University), Dr. E. Allen Herre (Smithsonian Tropical Research Institute, Panama), Dr. Charlotte Jandér (Harvard University), Dr. Carlos Machado (University of Maryland), and Dr. Robert Raguso (Cornell University).
Education: A PhD degree in biological sciences or bioinformatics, or acceptable equivalent combination of education and experience.
Experience/Skills: Experience working with genomic/transcriptomic/GBS datasets; demonstrated experience working in a Linux/Unix shell environment; competency with at least one scripting language (e.g., Perl, Python, R). Demonstrated experience in the phylogenetic and/or population genetic analysis of NGS data, ideally obtained via sequence capture or GBS/RAD-seq methods. Well-developed organizational and time management skills, and leadership ability to direct (with the PIs) a large and productive project.
Terms of Appointment
Starting salary is $45,000 plus benefits. Funds are available for one year and are renewable for up to four years, pending satisfactory progress. The optimal start date is June 1, 2016.
For consideration, applicants must apply by April 1, 2016. Informal inquiries are encouraged prior to formal application. For formal application, please send 1) a cover letter, 2) a curriculum vitae, 3) a brief statement of research experiences/interests, and 4) names and contact information for three references to Dr. John Nason (email@example.com).
Iowa State University is an Equal Opportunity/Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to race, color, age, religion, sex, sexual orientation, gender identity, genetic information, national origin, marital status, disability, or protected veteran status, and will not be discriminated against. Inquiries can be directed to the Director of Equal Opportunity, 3350 Beardshear Hall, (515) 294-7612.
Figs and their fig wasp pollinators and parasites have co-evolved for ~90 million years to become both highly diverse (>750 species of figs) and ecologically important “keystone” components of tropical forest ecosystems. Figs and wasps have long been assumed to represent a case of strict co-speciation, with highly specific pollinator and parasitic (non-pollinator) wasps identifying appropriate hosts via distinctive volatile chemical signals. More recent studies suggest a more complex scenario, however, involving an evolutionary history punctuated by host-shifts by individual wasp species. Although the wasp associations with fig hosts have been widely studied, the genetic consequences for the host figs of host-shifting pollinators and the mechanisms underlying host recognition remain poorly understood.
This project will fill these gaps by producing robust, detailed, many-gene phylogenies for 14 strangling fig (Ficus) species and their associated pollinating (Pegoscapus) and non-pollinating (Idarnes) fig wasps (~60 species) from the vicinity of Barro Colorado Island, Panama. Using transcriptome sequences, we will target ~300 genes from each of three species per lineage for capture and subsequent Illumina sequencing. Phylogenies will be inferred using Bayesian methods and will enable robust testing of phylogenetic congruence between figs and fig wasps. Further, they will guide population-level genotype by sequencing to test a priori predictions of potential cases of hybridization in the figs and host shifting and race formation in both pollinator and non-pollinator wasps. Combined with quantification of wasp-attracting fig volatiles and fruit-surface chemicals, this work will detect and resolve the genomic consequences of host introgression due to host-shifting pollinator wasps, and link them to the chemical basis of host-recognition.
This research will significantly clarify both the patterns and processes underlying the evolutionary ecology of fig and fig wasp interactions. Our standardized, genomic approach is essential for: 1) obtaining robust fig and fig wasp species trees, 2) delimiting fig species and discriminating cases of introgressive gene flow from shared ancestral polymorphism, and 3) linking introgression of figs and their chemical phenotypes to cases of pollinator host shifting. Our community-level approach is also essential to obtain the across-species replication necessary for robust statistical inference of diversification pattern and process across interacting fig and wasp taxa.