Job ID:
Job date: 2018-04-28
End Date: 2018-06-27
Company : University of Massachusetts Country : United States Role : Postdoc
Job date: 2018-04-28
End Date: 2018-06-27
Company : University of Massachusetts Country : United States Role : Postdoc
Job Description:
We are seeking a highly motivated, creative and independent individual to join our program to understand host-virus interactions and how these interactions the severity of infection. In a collaboration between the Finberg laboratory (Infectious disease, https://www.umassmed.edu/infdis/research/research-labs) and the Garber laboratory (Computational Biology, http://garberlab.umassmed.edu) we are pursuing a modeling, data centric, approach that integrates human single cell RNA-Seq data together with in-vitro cellular models. In this unique set-up, hypothesis arising from patient samples will be tested on in-vitro models, thus providing a unique opportunity for building, testing and refining computational models. The person hired for this position will lead the data analysis and modeling efforts and will be intimately involved in designing experiments to test model predictions. As such the ideal candidate will be intimately familiar with machine learning, sequencing technologies and have a working knowledge of molecular biology. Key responsibilities include:
Additional Info:
To apply, please forward CV, statement of research and contact information for three references to: Robert W. Finberg, MD via email at: Robert.Finberg@umassmed.edu[Click Here to Access the Original Job Post]
We are seeking a highly motivated, creative and independent individual to join our program to understand host-virus interactions and how these interactions the severity of infection. In a collaboration between the Finberg laboratory (Infectious disease, https://www.umassmed.edu/infdis/research/research-labs) and the Garber laboratory (Computational Biology, http://garberlab.umassmed.edu) we are pursuing a modeling, data centric, approach that integrates human single cell RNA-Seq data together with in-vitro cellular models. In this unique set-up, hypothesis arising from patient samples will be tested on in-vitro models, thus providing a unique opportunity for building, testing and refining computational models. The person hired for this position will lead the data analysis and modeling efforts and will be intimately involved in designing experiments to test model predictions. As such the ideal candidate will be intimately familiar with machine learning, sequencing technologies and have a working knowledge of molecular biology. Key responsibilities include:
- Responsible for analysis of single cell and bulk RNA-Seq data
- Statistical modeling of genomics data
- Development of computational tools for analysis of single cell RNA-Seq and other sequencing methods
- Design and analysis of loss and gain of function experiments to validate model predictions
- Use demonstrated scientific creativity, collaboration with others, and independent thought to expand technical capabilities and identify new research opportunities
Qualifications
REQUIRED QUALIFICATIONS:- PhD. in Bioinformatics, Computational Biology, Physics, Computer Science, Statistics or related field
- Working knowledge of molecular biology, sequencing technologies, and cell biology
- Fluency in at least one scripting language (e.g. Python, Perl) and good knowledge of non-scripting languages (e.g. Java, C++, Scala)
- Strong publication record and excellent communication skills
- Excellent organization and time management skills
- Must be able to handle a variety of tasks and to adapt to a highly dynamic environment
- Wet lab experience desirable
Requeriments :
Skills :
- Cell Biology
- genomic
- Machine Learning
- Modeling
- molecular biology
- Programing in C++
- Programing in Python
- Programming in Java
- Programming in PERL
- RNA-seq
- Statistics
Areas :
Additional Info:
To apply, please forward CV, statement of research and contact information for three references to: Robert W. Finberg, MD via email at: Robert.Finberg@umassmed.edu[Click Here to Access the Original Job Post]