Duke University is an Affirmative Action/Equal Opportunity Employer committed to providing employment opportunity without regard to an individual’s age, color, disability, genetic information, gender, gender identity, national origin, race, religion, sexual orientation, or veteran status.
The Phenoscape project “Semantics for Comparative Analysis of Trait Evolution” (SCATE; http://scate.phenoscape.org) is a collaborative NSF-funded effort that uses AI approaches powered by ontologies, machine reasoning, and graph-based similarity metrics to render the vast amount of published evolutionary phenotype descriptions amenable to large-scale computational data mining, inference, and probabilistic modeling. One of its key goals is to make accessing Phenoscape’s AI capabilities and data resources as easy and low barrier for users as, for example, cloud APIs have made accessing complex machine learning capabilities by programmers of smart phone apps.
To this end, we seek student interns to help with building out a programming interface between the data and capabilities of the Phenoscape Knowledgebase (http://kb.phenoscape.org) and the ecosystem of methods for comparative analysis of trait evolution within the popular R platform for statistical computing (http://r-project.org/). Specifically, the students would implement methods and reproducible vignettes in the R package Rphenoscape to turn user stories into executable code (https://github.com/phenoscape/rphenoscape).
The internship is in the group of Phenoscape PI Hilmar Lapp (ORCID: http://orcid.org/0000-0001-9107-0714), who is the Director of Informatics at Duke’s Center for Genomic and Computational Biology (GCB).
Qualifications and other information about this position:
- Technologies involved are primarily programming in R (for the Rphenoscape package), and communicating with HTTP REST-based web-services that return data in JSON format (the Phenoscape API). Proficiency in either is not required, but the student should be eager to pick up the level of skills needed that they don’t yet have.
- Experience with ontologies and machine reasoning is useful, but can also be acquired on the job.
- As all code developed by Phenoscape, Rphenoscape is a collaboratively developed open-source software hosted on Github. Code created as part of this project will be as well. Familiarity with version control (and in particular Git) is useful, as is experience with collaborative software development, but can also be learned as part of the job.
- Work-study eligibility is not required. Work hours can be flexible and are not to exceed 19.9 hours/week. Start date as soon as available.
- A work desk is available co-located with the GCB Informatics group in the North Building. If preferable, work can also be done remotely.
- Rate of pay is between $15-$20 per hour, depending on qualification and programming proficiency. Internships are semester-length by default. Depending on performance and interest of the student, renewal for additional semester(s) is possible.
If you are interested, please contact Hilmar Lapp (firstname.lastname@example.org) with your résumé.
Faculty Cluster Hire in Genomics and Human Genetics
Duke University seeks up to three exceptional, collaborative, and creative scientists to join its faculty in tenure/tenure-track positions. We invite applications from researchers with an outstanding track record in developing and applying statistical, computational, or experimental approaches to cutting-edge problems in genomics and human genetics.
Candidates should hold a PhD or equivalent degree in a quantitative or experimental discipline. We are particularly interested in scientists working in evolutionary/population genomics, functional genomics, genome technology development, medical genetics, and statistical/computational genomics.
We strongly encourage applications from scientists with a demonstrated interest in collaborative research. Successful candidates will synergize with existing strengths at Duke in medicine, engineering, environmental sciences, and basic sciences. The collaborative nature of these positions will provide successful candidates with access to exceptional resources, including substantial cluster computing infrastructure, strong core facilities, a diverse set of large biomedical datasets, and multidisciplinary partnerships.
Interested applicants should submit materials (cover letter, CV, and a statement of research accomplishments and interests) and ask three referees to submit reference letters at https://academicjobsonline.org/ajo/jobs/9837. Further inquiries may be directed to email@example.com. Review of applications will begin on November 15, 2017.
Molecular Genetics of Vascular Malformations
A post-doctoral position is available to investigate the role of somatic mutation in vascular malformation syndromes. This newly funded study will investigate vascular malformations that have been proposed to follow a two-hit mutation mechanism, as previously described by our laboratory for Cerebral Cavernous Malformations (CCM). See Akers et al., 2009, Human Molecular Genetics 18:919-930, PMC26402099, and McDonald et al., 2014. Human Molecular Genetics 23:4357-70, PMC4103679 for our published studies on CCM.
The ideal applicant will have previous experience with library construction for next-generation DNA sequencing and with analysis of the sequence data.
Please submit a cover letter outlining your professional interests, your CV, pdfs of up to three of your published papers, and the names and email addresses of three references to Douglas.Marchuk@duke.edu