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Statistics & Biostatistics Master’s Studentships in Ottawa

1 August 2017 Comments off

Reliable interpretation of genomic information makes unprecedented demands for innovations in statistical methodology and its application to biological systems. This unique opportunity drives research at the Evidence and Likelihood Lab of the Ottawa Institute of Systems Biology (http://www.davidbickel.com). David Bickel seeks new graduate students who will conduct original research involving the creation and evaluation of novel statistical tools for application to the analysis of transcriptomics, proteomics, metabolomics, and/or genome-wide-association data.

Each student will work toward an MSc degree in the Mathematics and Statistics Program at the University of Ottawa. MSc students have the additional option of choosing a Bioinformatics or Biostatistics Specialization. Financial support is available.

Intellectual curiosity and high mathematical aptitude are essential, as is the ability to quickly code and debug computer programs. Strong self motivation and good communication skills are also absolutely necessary. The following qualities are desirable but not required: coursework in bioinformatics, computer science, numerical methods, numerical analysis, software engineering, statistics, and/or biology; familiarly with R, S-PLUS, Stan, JAGS, Mathematica, C, Fortran, and/or LaTeX; experience with UNIX or Linux.

Canadians (by citizenship or permanent residency) are especially encouraged to apply, as are all exceptional students. To be considered, send a PDF CV that has your GPA and contact information of two references to dbickel@uOttawa.ca with a cover letter in the body of the message. Please indicate in the subject line of the message your immigration status (“Canadian citizen,” “Canadian PR,” or “visa”) and, optionally, a specialization (“Bioinformatics” or “Biostatistics”). Only those selected for further consideration will receive a response.

Categories: applications welcome

Undergraduate research project or internship

2 September 2016 Comments off

Acquire a statistical bioinformatics skill set by developing novel scientific software in the frontiers of genomics for high impact on medical science. Learn to analyze genomics data with newly created statistical methods. Make new biostatistics software accessible worldwide by improving the usability and functionality of the Statomics Lab’s data analysis code and by adding documentation. Providing scientists with these reliable biostatistical tools can advance medical research by improving the accuracy of conclusions drawn from genomics and clinical data.

Scientific breakthroughs from genome-sequencing projects brought the realization that reliable interpretation of the resulting information makes unprecedented demands for contemporaneous advances in computation and mathematical modeling. As the complexity of genomic data sets drives innovative statistics research, the Statomics Lab (http://davidbickel.com) aims to develop and apply novel methodology and algorithms to solve current problems in analyzing gene-expression, proteomics, metabolomics, SNP, ChIP-chip, and/or clinical data.

Intellectual curiosity and high mathematical aptitude are essential, as is the ability to quickly code and debug computer programs. Strong self motivation and good communication skills are also absolutely necessary. The following qualities are desirable but not required: coursework in bioinformatics, computer science, numerical methods, numerical analysis, software engineering, statistics, and/or biology; familiarly with BUGS, R, S-PLUS, C, Fortran, and/or LaTeX; experience with UNIX or Linux.

To be considered, send a PDF CV that has your GPA and contact information of two references to dbickel@uOttawa.ca with either “research project” or “internship” in the Subject line of the message and with a cover letter in the body of the message. Only those students selected for further consideration will receive a response.

Categories: applications welcome

Statistics & biostatistics graduate studentships

1 September 2016 Comments off

Reliable interpretation of genomic information makes unprecedented demands for innovations in statistical methodology and its application to biological systems. This unique opportunity drives research at the Statomics Lab of the Ottawa Institute of Systems Biology (http://davidbickel.com). The Statomics Lab seeks new graduate students who will conduct original research involving the creation and evaluation of novel statistical tools for application to the analysis of transcriptomics, proteomics, metabolomics, and/or genome-wide-association data.

Each student will work toward an MSc or PhD degree in the Mathematics and Statistics Program at the University of Ottawa. MSc students have the additional option of choosing a Bioinformatics or Biostatistics Specialization. Financial support is available.

Intellectual curiosity and high mathematical aptitude are essential, as is the ability to quickly code and debug computer programs. Strong self motivation and good communication skills are also absolutely necessary. The following qualities are desirable but not required: coursework in bioinformatics, computer science, numerical methods, numerical analysis, software engineering, statistics, and/or biology; familiarly with BUGS, R, S-PLUS, C, Fortran, and/or LaTeX; experience with UNIX or Linux.

Canadians (by citizenship or permanent residency) are especially encouraged to apply, as are all exceptional students. To be considered, send a PDF CV that has your GPA and contact information of two references to dbickel@uOttawa.ca with either “MSc” or “PhD” and any specialization in the Subject line of the message and with a cover letter in the body of the message. Only those selected for further consideration will receive a response.

Categories: applications welcome

Statistics & biostatistics graduate student stipends

1 February 2016 Comments off

Reliable interpretation of genomic information makes unprecedented demands for innovations in statistical methodology and its application to biological systems. This unique opportunity drives research at the Statomics Lab of the Ottawa Institute of Systems Biology (http://www.davidbickel.com/). The Statomics Lab seeks students who will conduct original research involving the application of novel statistical methods to the analysis transcriptomics, proteomics, metabolomics, and/or genome-wide-association data while earning a graduate degree in Mathematics and Statistics. The page https://davidbickel.com/career/ has information on careers in statistics and biostatistics.

Intellectual curiosity and high mathematical aptitude are essential, as is the ability to quickly code and debug computer programs. Strong self motivation, good communication skills, and a degree in bioinformatics, computer science, mathematics, physics, statistics, any field of engineering, or an equally quantitative field are also absolutely necessary. The following qualities are desirable but not required: coursework in computer science, numerical methods, numerical analysis, software engineering, statistics, and/or biology; familiarly with BUGS, R, S-PLUS, C, Fortran, and/or LaTeX; experience with UNIX or Linux.

To be considered, send a PDF CV that has your GPA and contact information of two references to dbickel@uOttawa.ca with the degree sought (MSc or PhD) in the Subject line of the message and with a cover letter in the body of the message. Only those students selected for further consideration will receive a response.

Categories: applications welcome

Postdoctoral position in statistical inference

23 September 2013 Comments off

Reliable interpretation of genomic and genetic information makes unprecedented demands for innovations in statistical methodology and its application to biological systems. This unique opportunity drives research at the Statomics Lab of the Ottawa Institute of Systems Biology; see http://www.statomics.com for details. The Statomics Lab seeks a postdoctoral fellow who will develop and apply novel methods of statistical inference to attack current problems in analyzing data from genome-wide association studies and related DNA sequence data. The successful candidate will conduct that research with guidance from David Bickel by building on modern empirical Bayes methods and/or higher-order asymptotics. The stipend will be CA$40,000/year, but as much as CA$50,000/year is possible for a candidate with exceptional qualifications. The fellowship is up to two years in duration conditional on satisfactory performance evaluations.

A solid foundation in statistical theory is essential, as is the ability to quickly develop reliable software implementing the statistical methods to be developed. Self-motivation, excellent communication skills, and reception of a PhD or equivalent doctorate in statistical genetics, statistics, bioinformatics, or a closely related field are also absolutely necessary. In addition, experience in empirical Bayes methodology, higher-order asymptotics (via likelihood or bootstrapping), or statistical genetics is highly desirable.

To apply, send a cover letter that summarizes your qualifications, a CV in PDF format, and contact information of three references to dbickel@uottawa.ca. Please write “Postdoctoral Position” and the year of your graduation or anticipated graduation in the subject field of the message. All applicants are thanked in advance; only those selected for further consideration will receive a response.

Postdoctoral training in Bayesian genomics

27 July 2011 Comments off

Reliable interpretation of genomic information makes unprecedented demands for innovations in statistical methodology and its application to biological systems. This unique opportunity drives research at the Statomics Lab of the Ottawa Institute of Systems Biology (http://www.statomics.com) to marshal strengths of robust Bayesian, empirical Bayes, and frequentist frameworks. The lab seeks a postdoctoral fellow who will collaboratively develop and apply novel methods of Bayesian inference to overcome current challenges in learning from genome-wide association data, high-dimensional gene expression data, and other data related to genomics.

Experience in computationally intensive data analysis is essential, as is the ability to quickly design and code reliable software implementing Markov chain Monte Carlo algorithms. Strong initiative, excellent communication skills, and reception of a PhD or equivalent doctorate in statistical genetics, statistics, bioinformatics, computer science, mathematics, physics, any field of engineering, or an equally quantitative field within four years prior to the start date are also absolutely necessary. The following qualities are desirable but not required: working knowledge of statistical genetics or genomics; familiarly with R, S-PLUS, Mathematica, C, Fortran, and/or LaTeX; experience in a UNIX or Linux environment.

To apply, send a PDF CV that has contact information of three references to dbickel@uottawa.ca, with “Bayes Postdoc” and the year of your graduation or anticipated graduation in the subject field of the message. In the message body, concisely present evidence that you meet each requirement for the position and describe your most significant papers and software packages with summaries of your contributions to them. All applicants are thanked in advance; only those selected for further consideration will receive a response.

Postdoctoral training in statistical inference

11 January 2011 Comments off

Reliable interpretation of genomic information makes unprecedented demands for innovations in statistical methodology and its application to biological systems. This unique opportunity drives research at the Statomics Lab of the Ottawa Institute of Systems Biology (http://www.statomics.com) to marshal strengths of the frequentist, empirical Bayes, and Bayesian frameworks. The Statomics Lab seeks a postdoctoral fellow who will collaboratively develop and apply novel methods of statistical inference to overcome current challenges in learning from genome-wide association data, neurodegenerative lipidomics data, and other data related to genomics.

Experience in computationally intensive data analysis is essential, as is the ability to quickly develop reliable software to implement the statistical algorithms developed. Strong initiative, excellent communication skills, and reception of a PhD or equivalent doctorate in statistical genetics, statistics, bioinformatics, computer science, mathematics, physics, any field of engineering, or an equally quantitative field within four years prior to the start date are also absolutely necessary. The following qualities are desirable but not required: working knowledge of statistical genetics; familiarly with R, S-PLUS, Mathematica, C, Fortran, and/or LaTeX; experience in a UNIX or Linux environment.

To apply, send a PDF CV that has contact information of three references to dbickel@uottawa.ca, with “Statistics Postdoctoral Fellowship” and the year of your graduation or anticipated graduation in the subject field of the message. In the message body, concisely present evidence that you meet each requirement for the position and describe your most significant papers and software packages with summaries of how you contributed to them. All applicants are thanked in advance; only those selected for further consideration will receive a response.