Job ID: 5735
Job date: 2016-07-10
End Date:
Company : Cold Spring Harbor Laboratory Country : Role : Postdoc
Job date: 2016-07-10
End Date:
Company : Cold Spring Harbor Laboratory Country : Role : Postdoc
Job Description:
Postdoctoral Positions in Computational Genomics.
Postdoctoral positions are available in Dr. Adam Siepel’s research group in its new location at the Simons Center for Quantitative Biology at Cold Spring Harbor Laboratory.
The Siepel Group specializes in the development of probabilistic models, algorithms for inference, prediction methods, and application of these methods in large-scale genomic data analysis. Of particular interest is research relevant to existing, NIH - and NSF -supported projects in human population genomics , including demography inference using Bayesian coalescent-based methods, inference of natural selection on regulatory and other noncoding sequences, and prediction of fitness consequences for noncoding mutations.
Relevant recent papers include the following:
Kuhlwilm M, Gronau I, Hubisz MJ, de Filippo C, Prado J, et al. Ancient gene flow from early modern humans into Eastern Neanderthals. Nature, 530(7591): 429–433, 2016.
Gulko B, Hubisz MJ, Gronau I, Siepel A. A method for calculating probabilities of fitness consequences for point mutations across the human genome. Nat. Genet. 47(3): 276–283, 2015.
Rasmussen MD, Hubisz MJ, Gronau I, Siepel A. Genome-wide inference of ancestral recombination graphs. PLOS Genet. 2014. 10(5): e1004342. PMCID : PMC4022496.
Arbiza L, Gronau I, Aksoy BA, Hubisz MJ, Gulko B, Keinan A, Siepel A. Genome-wide inference of natural selection on human transcription factor binding sites. Nat. Genet. 2013. 45(7): 723-729. PMCID : PMC3932982.
Gronau I, Arbiza L, Mohammed J, Siepel A. Inference of natural selection from interspersed genomic elements based on polymorphism and divergence. Mol. Biol. Evol. 2013. 30(5): 1159-1171. PMCID : PMC3697874.
Gronau I, Hubisz MJ, Gulko B, Danko CG, Siepel A. Bayesian inference of ancient human demography from individual genome sequences. Nat. Genet. 2011. 43(10): 1031-1034. PMCID : PMC3245873.
The ideal candidate will be enthusiastic, highly motivated and independent; will have a strong background in comparative genomics, population genomics, or phylogenetics, a serious interest in genetics combined with good skills in mathematics and computer science, and a strong record of accomplishment in research. Postdoctoral associates in the group are expected to participate in both methods development and data analysis, to be comfortable in a fast-moving, interactive, and collaborative research environment, and to actively publish and present results.
Position Requirements
Required Qualifications:
• Ph.D. in bioinformatics, computer science, statistics, genetics, molecular biology, applied mathematics, or a related field.
• Research experience (with first-author publications) in computational genomics or a closely related field.
• Fluency in probabilistic modeling and computational statistics.
• Proficiency in programming, ideally in C or C++, as well as in scripting languages such as python, Perl, mat lab, or R. Should be comfortable in a Linux environment, with large data sets, computer clusters, and databases.
To Apply:
Interested candidates must apply for this position via the CSHL careers website at: https://cshl.peopleadmin.com/postings/9898
Position Number 01229-R
Informal inquiries are also welcome.
Please submit a CV, a short description of research interests and experience, and contact information for three references by e-mail to asiepel@cshl.edu.
Adam Siepel, Ph.D.
Simons Center for Quantitative Biology
Cold Spring Harbor Laboratory
One Bungtown Road
Cold Spring Harbor, NY 11724
For additional information about CSHL please visit: https://www.cshl.edu
CSHL is an EO/AA Employer. All qualified applicants will receive consideration for employment and will not be discriminated against on the basis of race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability or protected veteran status.
VEVRAA Federal Contractor.
Additional Info:
[Click Here to Access the Original Job Post]
Postdoctoral Positions in Computational Genomics.
Postdoctoral positions are available in Dr. Adam Siepel’s research group in its new location at the Simons Center for Quantitative Biology at Cold Spring Harbor Laboratory.
The Siepel Group specializes in the development of probabilistic models, algorithms for inference, prediction methods, and application of these methods in large-scale genomic data analysis. Of particular interest is research relevant to existing, NIH - and NSF -supported projects in human population genomics , including demography inference using Bayesian coalescent-based methods, inference of natural selection on regulatory and other noncoding sequences, and prediction of fitness consequences for noncoding mutations.
Relevant recent papers include the following:
Kuhlwilm M, Gronau I, Hubisz MJ, de Filippo C, Prado J, et al. Ancient gene flow from early modern humans into Eastern Neanderthals. Nature, 530(7591): 429–433, 2016.
Gulko B, Hubisz MJ, Gronau I, Siepel A. A method for calculating probabilities of fitness consequences for point mutations across the human genome. Nat. Genet. 47(3): 276–283, 2015.
Rasmussen MD, Hubisz MJ, Gronau I, Siepel A. Genome-wide inference of ancestral recombination graphs. PLOS Genet. 2014. 10(5): e1004342. PMCID : PMC4022496.
Arbiza L, Gronau I, Aksoy BA, Hubisz MJ, Gulko B, Keinan A, Siepel A. Genome-wide inference of natural selection on human transcription factor binding sites. Nat. Genet. 2013. 45(7): 723-729. PMCID : PMC3932982.
Gronau I, Arbiza L, Mohammed J, Siepel A. Inference of natural selection from interspersed genomic elements based on polymorphism and divergence. Mol. Biol. Evol. 2013. 30(5): 1159-1171. PMCID : PMC3697874.
Gronau I, Hubisz MJ, Gulko B, Danko CG, Siepel A. Bayesian inference of ancient human demography from individual genome sequences. Nat. Genet. 2011. 43(10): 1031-1034. PMCID : PMC3245873.
The ideal candidate will be enthusiastic, highly motivated and independent; will have a strong background in comparative genomics, population genomics, or phylogenetics, a serious interest in genetics combined with good skills in mathematics and computer science, and a strong record of accomplishment in research. Postdoctoral associates in the group are expected to participate in both methods development and data analysis, to be comfortable in a fast-moving, interactive, and collaborative research environment, and to actively publish and present results.
Position Requirements
Required Qualifications:
• Ph.D. in bioinformatics, computer science, statistics, genetics, molecular biology, applied mathematics, or a related field.
• Research experience (with first-author publications) in computational genomics or a closely related field.
• Fluency in probabilistic modeling and computational statistics.
• Proficiency in programming, ideally in C or C++, as well as in scripting languages such as python, Perl, mat lab, or R. Should be comfortable in a Linux environment, with large data sets, computer clusters, and databases.
To Apply:
Interested candidates must apply for this position via the CSHL careers website at: https://cshl.peopleadmin.com/postings/9898
Position Number 01229-R
Informal inquiries are also welcome.
Please submit a CV, a short description of research interests and experience, and contact information for three references by e-mail to asiepel@cshl.edu.
Adam Siepel, Ph.D.
Simons Center for Quantitative Biology
Cold Spring Harbor Laboratory
One Bungtown Road
Cold Spring Harbor, NY 11724
For additional information about CSHL please visit: https://www.cshl.edu
CSHL is an EO/AA Employer. All qualified applicants will receive consideration for employment and will not be discriminated against on the basis of race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability or protected veteran status.
VEVRAA Federal Contractor.
Requeriments :
Skills :
- Bioinformatics
- Biology
- Genetics
- Modeling
- Programing in C
- Programing in C++
- Programing in Python
- Programing Skills
- Programming in Matlab
- Programming in PERL
- Programming in R
- Statistics
Areas :
Additional Info:
[Click Here to Access the Original Job Post]