Job ID: 6709
Job date: 2017-02-11
End Date:
Company : Children s Hospital of Philadelphia Country : Role : Research Scientist
Job date: 2017-02-11
End Date:
Company : Children s Hospital of Philadelphia Country : Role : Research Scientist
Job Description:
The Bioinformatics Scientist II position is an entry level position for a PhD level professional and a 2nd stage position for those with moderate experience without a PhD. The focus of the position is service-level application of bioinformatics tools and methods to bench and clinical research problems in various biomedical domains. The position allows for a wide variety of activities described within the job responsibilities and encompasses positions within both research and clinical environments. Activities occur with a moderate degree of supervision with some latitude for independent judgment, development of bioinformatics workflows and processes, and presentation of results. The Bioinformatics Scientist II will begin to apply best practices in collaborative science as a bioinformatics domain expert. Academic output, while not a primary focus of this position, is also expected with a moderate degree of supervision. The Bioinformatics Scientist II is primarily focused on supporting scientific teams and projects as a bioinformatics domain expert. The Bioinformatics Scientist II must be able to perform all responsibilities listed in the Bioinformatics Scientist I job description. All responsibilities listed in this description are additional. Job Responsibilities: Pre-Analysis (20%): Contribute to the development of application portfolio by developing knowledge of internally developed systems, open-source programs, and commercial applications. Provide efficient data management support. -Use standard pipelines for data processing and manipulation in advance of performing analysis in a manner that best enables the analysis plan. -Contribute to the development of additional pipeline functionality and changes by providing knowledge of both collaboration-specific requirements and bioinformatics discipline advances. -Advocate for specific collaboration requirements for continual advancement of shared pipeline and code resources. -Provide collaboration-specific transparency for data processing and pre-analysis, including sample- and cohort-level status. Coding (20%): Code and generally support code and applications on behalf of collaborative project and/or team. -Within the context of the collaboration or project, develop and apply best practices to code development: .Establish requirements with the project team. .Review existing applications and code sources (both commercial and open source) and selection of best strategy for development or adoption. .Advocate for chosen strategy to project team by showing value of approach. -Develop best practices for project-based code development, QC, and execution consist with the expectations of specific collaborations. -Regularly seek peer-to-peer code reviews by participating in informal and formal critical code reviews. -Data Analysis (20%): Analyze data of high complexity by applying sound statistical and commonly accepted bioinformatics methods to -omics data primarily under the direction of the collaborative project team Develop robust analysis plans independently with regular peer-to-peer review in both informal and formal settings Incorporate more advanced applications and methods into analysis Develop at least one “specialty” analytical or biomedical area that serves the collaborative team Collaboration (20%): Establish role within collaborative project team as primary bioinformatics resource -Contribute to and influence project-level management by serving as bioinformatics point. -Define and promote boundaries of support by assessing all stakeholders, including bioinformatics management, collaborator expectations, and funding levels and mechanisms. -Regularly discuss satisfaction and expectations with collaborators; continually advocate for clear understanding of role. -Develop new collaborations with high degree of supervision. Academic Output (20%): Develop presentations, grant sections, and manuscript sections with subsequent review by peers and mentors. -Regularly contribute to bioinformatics-focused manuscripts and publications. -Regularly contribute to podium presentations and posters. -Contribute to bioinformatics sections of grant and award proposals. Required Education and Experience: -BS/MS/PhD in biological or computational discipline. -3-7 years’ experience in applied bioinformatics, genomics, and computational work. This experience can be inclusive of a relevant PhD dissertation. -Strong UNIX/LINUX expertise required. -Proficiency in R or similar commonly used bioinformatics language required. -Experience with management and analysis of complex data types required. -Proficiency in various open source and commercial bioinformatics resources and software required. -Familiarity with resources of genomic data sets and analysis tools, such as UCSC Genome Browser, Bioconductor, ENCODE, and NCBI databases is required. Preferred Education, Experience & Cert/Lic: -Experience with Python, Perl, or other languages preferred. -Experience with pipeline or workflow development frameworks preferred. -Experience or knowledge of technologies commonly used in biological labs, such as PCR, cloning, electrophoresis gels, and cell culture preferred. -Knowledge of the working mechanism of microarray, NGS, mass spectrometry, or other high-throughput technologies and awareness of their strengths and weaknesses, as well as applicability to a specific biological problem is preferred. -Ability to correctly select and perform statistical tests for most types of genomic data, and to properly interpret their results in the scenario of a specific study is preferred. Additional Technical Requirements: -Ability to interact with biologists and clinicians during a scientific discussion is required. -Accountability and attention to timelines. -Excellent organization and communication skills with an emphasis on strong presentation skills. -Ability to independently plan and execute analyses of moderate complexity required. -Ability to provide objective validation of results required. -Ability to work in a team environment.
Additional Info:
[Click Here to Access the Original Job Post]
The Bioinformatics Scientist II position is an entry level position for a PhD level professional and a 2nd stage position for those with moderate experience without a PhD. The focus of the position is service-level application of bioinformatics tools and methods to bench and clinical research problems in various biomedical domains. The position allows for a wide variety of activities described within the job responsibilities and encompasses positions within both research and clinical environments. Activities occur with a moderate degree of supervision with some latitude for independent judgment, development of bioinformatics workflows and processes, and presentation of results. The Bioinformatics Scientist II will begin to apply best practices in collaborative science as a bioinformatics domain expert. Academic output, while not a primary focus of this position, is also expected with a moderate degree of supervision. The Bioinformatics Scientist II is primarily focused on supporting scientific teams and projects as a bioinformatics domain expert. The Bioinformatics Scientist II must be able to perform all responsibilities listed in the Bioinformatics Scientist I job description. All responsibilities listed in this description are additional. Job Responsibilities: Pre-Analysis (20%): Contribute to the development of application portfolio by developing knowledge of internally developed systems, open-source programs, and commercial applications. Provide efficient data management support. -Use standard pipelines for data processing and manipulation in advance of performing analysis in a manner that best enables the analysis plan. -Contribute to the development of additional pipeline functionality and changes by providing knowledge of both collaboration-specific requirements and bioinformatics discipline advances. -Advocate for specific collaboration requirements for continual advancement of shared pipeline and code resources. -Provide collaboration-specific transparency for data processing and pre-analysis, including sample- and cohort-level status. Coding (20%): Code and generally support code and applications on behalf of collaborative project and/or team. -Within the context of the collaboration or project, develop and apply best practices to code development: .Establish requirements with the project team. .Review existing applications and code sources (both commercial and open source) and selection of best strategy for development or adoption. .Advocate for chosen strategy to project team by showing value of approach. -Develop best practices for project-based code development, QC, and execution consist with the expectations of specific collaborations. -Regularly seek peer-to-peer code reviews by participating in informal and formal critical code reviews. -Data Analysis (20%): Analyze data of high complexity by applying sound statistical and commonly accepted bioinformatics methods to -omics data primarily under the direction of the collaborative project team Develop robust analysis plans independently with regular peer-to-peer review in both informal and formal settings Incorporate more advanced applications and methods into analysis Develop at least one “specialty” analytical or biomedical area that serves the collaborative team Collaboration (20%): Establish role within collaborative project team as primary bioinformatics resource -Contribute to and influence project-level management by serving as bioinformatics point. -Define and promote boundaries of support by assessing all stakeholders, including bioinformatics management, collaborator expectations, and funding levels and mechanisms. -Regularly discuss satisfaction and expectations with collaborators; continually advocate for clear understanding of role. -Develop new collaborations with high degree of supervision. Academic Output (20%): Develop presentations, grant sections, and manuscript sections with subsequent review by peers and mentors. -Regularly contribute to bioinformatics-focused manuscripts and publications. -Regularly contribute to podium presentations and posters. -Contribute to bioinformatics sections of grant and award proposals. Required Education and Experience: -BS/MS/PhD in biological or computational discipline. -3-7 years’ experience in applied bioinformatics, genomics, and computational work. This experience can be inclusive of a relevant PhD dissertation. -Strong UNIX/LINUX expertise required. -Proficiency in R or similar commonly used bioinformatics language required. -Experience with management and analysis of complex data types required. -Proficiency in various open source and commercial bioinformatics resources and software required. -Familiarity with resources of genomic data sets and analysis tools, such as UCSC Genome Browser, Bioconductor, ENCODE, and NCBI databases is required. Preferred Education, Experience & Cert/Lic: -Experience with Python, Perl, or other languages preferred. -Experience with pipeline or workflow development frameworks preferred. -Experience or knowledge of technologies commonly used in biological labs, such as PCR, cloning, electrophoresis gels, and cell culture preferred. -Knowledge of the working mechanism of microarray, NGS, mass spectrometry, or other high-throughput technologies and awareness of their strengths and weaknesses, as well as applicability to a specific biological problem is preferred. -Ability to correctly select and perform statistical tests for most types of genomic data, and to properly interpret their results in the scenario of a specific study is preferred. Additional Technical Requirements: -Ability to interact with biologists and clinicians during a scientific discussion is required. -Accountability and attention to timelines. -Excellent organization and communication skills with an emphasis on strong presentation skills. -Ability to independently plan and execute analyses of moderate complexity required. -Ability to provide objective validation of results required. -Ability to work in a team environment.
Requeriments :
Skills :
- Bioinformatics
- genomic
- Lunix/Unix
- Microarray
- Next Generation Sequencing
- Programing in Python
- Programing Skills
- Programming in PERL
- Programming in R
- Statistics
Areas :
Additional Info:
[Click Here to Access the Original Job Post]