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Postdoctoral researcher - Machine learning in human genomics
We are seeking a talented and driven postdoctoral fellow to join the laboratory of Jake Michaelson, PhD, in the department of psychiatry at the University of Iowa.
The Michaelson lab investigates the effect of genetic variation on the development and function of the brain, particularly in the context of neurodevelopmental conditions such as autism and language impairment. Our work revolves mostly around integrating information from large scale data sets (e.g., whole genome sequencing, RNA-seq, ChIP-seq, etc.) and deriving informative features so that predictive models can be built and used to better understand the molecular basis of neurodevelopmental conditions. The Michaelson lab is highly multidisciplinary and includes elements of human subjects recruitment and research, experimental work with model organisms, and computational modeling.
This postdoctoral position will be devoted mostly to our work in uncovering the genetic and molecular basis of human language through analysis of whole genome sequencing (WGS) data. In particular, the candidate will be expected to perform analyses that integrate our WGS data with other forms of data in order to explore new hypotheses about the genetic basis of language. Candidates with a doctoral degree in human genetics, quantitative genetics, bioinformatics, computational biology, or other fields with strong quantitative skills (e.g., biostatistics, statistics, or computer science) will be considered. Demonstrated experience in machine learning or applied statistical modeling is required. The candidate will serve as an in-lab mentor for several graduate students with respect to machine learning and statistics, and is therefore expected to be knowledgeable in these topics and able to teach them in a lucid way.
This position requires good scientific programming skills (R strongly preferred) with a commitment to the principles of clear documentation and reproducible research. Experience with databases (e.g. MySQL) is a plus. Candidates who can demonstrate skills in effective data visualization will be given preference. Excellent communication and presentation skills are required.
Qualified applicants should send curriculum vitae, a brief statement of research interests, and three references to Jake Michaelson at [email protected].
The University of Iowa is an Equal Opportunity/Affirmative Action Employer. Applications from women and minorities are encouraged.
We are seeking a talented and driven postdoctoral fellow to join the laboratory of Jake Michaelson, PhD, in the department of psychiatry at the University of Iowa.
The Michaelson lab investigates the effect of genetic variation on the development and function of the brain, particularly in the context of neurodevelopmental conditions such as autism and language impairment. Our work revolves mostly around integrating information from large scale data sets (e.g., whole genome sequencing, RNA-seq, ChIP-seq, etc.) and deriving informative features so that predictive models can be built and used to better understand the molecular basis of neurodevelopmental conditions. The Michaelson lab is highly multidisciplinary and includes elements of human subjects recruitment and research, experimental work with model organisms, and computational modeling.
This postdoctoral position will be devoted mostly to our work in uncovering the genetic and molecular basis of human language through analysis of whole genome sequencing (WGS) data. In particular, the candidate will be expected to perform analyses that integrate our WGS data with other forms of data in order to explore new hypotheses about the genetic basis of language. Candidates with a doctoral degree in human genetics, quantitative genetics, bioinformatics, computational biology, or other fields with strong quantitative skills (e.g., biostatistics, statistics, or computer science) will be considered. Demonstrated experience in machine learning or applied statistical modeling is required. The candidate will serve as an in-lab mentor for several graduate students with respect to machine learning and statistics, and is therefore expected to be knowledgeable in these topics and able to teach them in a lucid way.
This position requires good scientific programming skills (R strongly preferred) with a commitment to the principles of clear documentation and reproducible research. Experience with databases (e.g. MySQL) is a plus. Candidates who can demonstrate skills in effective data visualization will be given preference. Excellent communication and presentation skills are required.
Qualified applicants should send curriculum vitae, a brief statement of research interests, and three references to Jake Michaelson at [email protected].
The University of Iowa is an Equal Opportunity/Affirmative Action Employer. Applications from women and minorities are encouraged.