Job ID: 48435
Job date: 2017-12-22
End Date:
Company : George Washington University Country : Role : Research Scientist
Job date: 2017-12-22
End Date:
Company : George Washington University Country : Role : Research Scientist
Job Description:
The George Washington University, Department of Environmental and Occupational Health is looking for a Research Associate to join our molecular epidemiology and microbiome research group. The successful candidate will have a unique opportunity to work with a multidisciplinary team comprising clinicians, microbiologists, epidemiologists, and bioinformaticists on a wide range of microbial ecologic and genomic research projects. Our team uses innovative, multi-disciplinary methods to: 1. Evaluate the role of host-associated microbial communities on pathogen transmission and on host susceptibility to colonization and infection by pathogens ranging from HIV, Staphylococcus aureus, to extra-intestinal pathogenic Escherichia coli (ExPEC); and 2. Determine the contribution of environmental reservoirs (particularly of food and food animals) to the colonization and infection by antibiotic-resistant pathogens in humans; 3. Develop novel strategies (such as probiotics) for the prevention and treatment of infectious diseases. We are seeking a highly motivated and skilled scientist to contribute to multiple NIH-funded microbiome research projects. The successful applicant will have experience with microbial ecology or computational biology research, a collaborative attitude, strong self-management skills, ability to work independently and with a team. The successful applicant must be able to manage his/her time across multiple projects. Individuals with strong track record in ecological modeling and machine-learning techniques are strongly encouraged to apply. Previous experience in human microbial ecology is not required. Individuals with track record solely in environmental microbial ecology or other related ecological or computational biology fields are welcome to apply. The initial appointment is for one year. Responsibilities include: • Develop ecological/bioinformatics models and methods for analysis of microbiome, genomic, and multi-omic datasets, • Apply existing and/or new analytical methods to large-scale data sets from multiple longitudinal cohort studies with guidance from the PI and collaborators, • Perform study coordination functions, including preparation of study and IRB protocol and grant reports with guidance from the PI, • Participate in one of the following lab-wide initiatives: (i) development of in-house web-based database for sample/metadata organization and integration with data processing/analysis and (ii) development of liquid-handling robot instructional programs for automating laboratory workflows, • Assist or lead the preparation of grant applications, manuscripts, and presentations. • Performs other related duties as assigned. The omission of specific duties does not preclude the supervisor from assigning duties that are logically related to the position. Minimum Qualifications: Qualified candidates will hold a master’s degree and 1 year of experience in a related discipline. Degree must be conferred by the start date of the position. Preferred Qualifications: • Masters in Ecology, Computational Biology, Bioinformatics, or related field. • Undergraduate or graduate coursework in Microbiology, Biology, or related topics such as Epidemiology. • At least 1 year experience in Ecology or Computational Biology research. • Experience in data visualization and analysis, preferably applied towards large microbial ecological datasets. • Knowledge of Unix/Linux/Mac OS X/Windows platforms. • Proficiency in statistical softwares/programs such as Matlab, or R/S-plus. • Experience in manuscript and abstract preparation. • Strong analytical and troubleshooting skills and experience or interest in working in a multidisciplinary team setting. • Demonstrated computer-programming skills in Java and scripting languages such as C, Perl and/or Python. • Strong publication record, especially first-author manuscript(s). • Experience in phylogenetic, comparative genomic analysis, or bacterial genome assembly and annotation. • Ability to apply ecological modeling and machine learning techniques to solve “big data” problems • Experience with high-performance computing environment. • Experience with building web applications using PHP, Laravel and/or Ruby, Ruby On Rails. • Experience working with Javascript, JQuery, HTML, HTML5, CCS, CSS3, Bootstrap, MySQL
Additional Info:
Background Screening: Successful Completion of a Background Screening will be required as a condition of hire. EEO Statement: The university is an Equal Employment Opportunity/Affirmative Action employer that does not unlawfully discriminate in any of its programs or activities on the basis of race, color, religion, sex, national origin, age, disability, veteran status, sexual orientation, gender identity or expression, or on any other basis prohibited by applicable law.[Click Here to Access the Original Job Post]
The George Washington University, Department of Environmental and Occupational Health is looking for a Research Associate to join our molecular epidemiology and microbiome research group. The successful candidate will have a unique opportunity to work with a multidisciplinary team comprising clinicians, microbiologists, epidemiologists, and bioinformaticists on a wide range of microbial ecologic and genomic research projects. Our team uses innovative, multi-disciplinary methods to: 1. Evaluate the role of host-associated microbial communities on pathogen transmission and on host susceptibility to colonization and infection by pathogens ranging from HIV, Staphylococcus aureus, to extra-intestinal pathogenic Escherichia coli (ExPEC); and 2. Determine the contribution of environmental reservoirs (particularly of food and food animals) to the colonization and infection by antibiotic-resistant pathogens in humans; 3. Develop novel strategies (such as probiotics) for the prevention and treatment of infectious diseases. We are seeking a highly motivated and skilled scientist to contribute to multiple NIH-funded microbiome research projects. The successful applicant will have experience with microbial ecology or computational biology research, a collaborative attitude, strong self-management skills, ability to work independently and with a team. The successful applicant must be able to manage his/her time across multiple projects. Individuals with strong track record in ecological modeling and machine-learning techniques are strongly encouraged to apply. Previous experience in human microbial ecology is not required. Individuals with track record solely in environmental microbial ecology or other related ecological or computational biology fields are welcome to apply. The initial appointment is for one year. Responsibilities include: • Develop ecological/bioinformatics models and methods for analysis of microbiome, genomic, and multi-omic datasets, • Apply existing and/or new analytical methods to large-scale data sets from multiple longitudinal cohort studies with guidance from the PI and collaborators, • Perform study coordination functions, including preparation of study and IRB protocol and grant reports with guidance from the PI, • Participate in one of the following lab-wide initiatives: (i) development of in-house web-based database for sample/metadata organization and integration with data processing/analysis and (ii) development of liquid-handling robot instructional programs for automating laboratory workflows, • Assist or lead the preparation of grant applications, manuscripts, and presentations. • Performs other related duties as assigned. The omission of specific duties does not preclude the supervisor from assigning duties that are logically related to the position. Minimum Qualifications: Qualified candidates will hold a master’s degree and 1 year of experience in a related discipline. Degree must be conferred by the start date of the position. Preferred Qualifications: • Masters in Ecology, Computational Biology, Bioinformatics, or related field. • Undergraduate or graduate coursework in Microbiology, Biology, or related topics such as Epidemiology. • At least 1 year experience in Ecology or Computational Biology research. • Experience in data visualization and analysis, preferably applied towards large microbial ecological datasets. • Knowledge of Unix/Linux/Mac OS X/Windows platforms. • Proficiency in statistical softwares/programs such as Matlab, or R/S-plus. • Experience in manuscript and abstract preparation. • Strong analytical and troubleshooting skills and experience or interest in working in a multidisciplinary team setting. • Demonstrated computer-programming skills in Java and scripting languages such as C, Perl and/or Python. • Strong publication record, especially first-author manuscript(s). • Experience in phylogenetic, comparative genomic analysis, or bacterial genome assembly and annotation. • Ability to apply ecological modeling and machine learning techniques to solve “big data” problems • Experience with high-performance computing environment. • Experience with building web applications using PHP, Laravel and/or Ruby, Ruby On Rails. • Experience working with Javascript, JQuery, HTML, HTML5, CCS, CSS3, Bootstrap, MySQL
Requeriments :
Skills :
- Biology
- Computational Biology
- HPC
- HTML
- JavaScript
- Lunix/Unix
- Machine Learning
- Microbiology
- Modeling
- MySQL
- PHP
- Programing in C
- Programing in Python
- Programing Skills
- Programming in Java
- Programming in Matlab
- Programming in PERL
- Programming in R
Areas :
Additional Info:
Background Screening: Successful Completion of a Background Screening will be required as a condition of hire. EEO Statement: The university is an Equal Employment Opportunity/Affirmative Action employer that does not unlawfully discriminate in any of its programs or activities on the basis of race, color, religion, sex, national origin, age, disability, veteran status, sexual orientation, gender identity or expression, or on any other basis prohibited by applicable law.[Click Here to Access the Original Job Post]