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Position: Research Fellow: Single cell transcriptomics of cell cycle heterogeneity and cell fate choice
Institution: University College London
Department: Division of Biosciences
Location: London, United Kingdom
Duties: Your aim will be to reconstruct gene network dynamics to follow their temporal changes in gene activity in individual cells from different cell cycle positions as they differentiate along different linages. You will develop novel computational and statistical methods (e.g. gene network identification, pseudotime, machine learning) to characterize the dynamics of gene network activity, and capture temporal changes in gene network activity in individual cells from different cell cycle stages as they differentiate. Live imaging of transcription and molecular genetic approaches to modify network activity in genetically modified cells will be used to validate your findings
Requirements: Candidates with extensive experience of using either computational genomic approaches or wet lab approaches to understand the molecular basis of gene networks will be considered. You should currently hold or be about to obtain a PhD in Computational, Cell, Molecular or Developmental Biology. Proven knowledge of research techniques and methodologies, evidence of a publication record in good quality publications and practical experience of applying specialist skills and techniques are also Essential Criteria
   
Text: Research Fellow: Single cell transcriptomics of cell cycle heterogeneity and cell fate choice, - Ref:1782567 Click here to go back to search results Apply Now UCL Department / Division Division of Biosciences Specific unit / Sub department Research Department of Genetics, Evolution and Environment Location of position London Grade 7 Hours Full Time Salary (inclusive of London allowance) ?35,328 - ?42,701 per annum Duties and Responsibilities Based in the Faculty of Life Sciences UCL Biosciences is one of the UKs largest and most active divisions for research and education in the biological sciences. We are currently seeking a Research Fellow working on understanding gene network heterogeneity in development. Recently, we found that cell-cell variation in cell cycle position facilitates symmetry breaking during development, as it primes cells to respond to different differentiation cues (Gruenheit et al, Developmental Cell, 2018). You will perform single cell gene expression analysis to understand the molecular mechanisms underlying this cell cycle control of cell fate choice you. For this, you will utilise our recently generated single cell RNA-seq dataset in which gene expression in 1000s of single cells was generated at different times after receiving differentiation cues. Your aim will be to reconstruct gene network dynamics to follow their temporal changes in gene activity in individual cells from different cell cycle positions as they differentiate along different linages. You will develop novel computational and statistical methods (e.g. gene network identification, pseudotime, machine learning) to characterize the dynamics of gene network activity, and capture temporal changes in gene network activity in individual cells from different cell cycle stages as they differentiate. Live imaging of transcription and molecular genetic approaches to modify network activity in genetically modified cells will be used to validate your findings. You will also develop predictive models to understand the mechanism controlling cell fate choice. This will include computer simulation of the molecular basis of cell cycle control of differentiation. High throughput live cell imaging to quantify the differentiation behaviour of cells at different cell cycle phases will be used to test these models. This framework will be fundamental in generating new hypothesis guiding future experiments. You will join a multidisciplinary team led by Professor Chris Thompson. The approaches used in the lab include transcriptomics, functional genomics, molecular genetics, live cell imaging and mathematical modelling. The post is funded until 29/02/2020 in the first instance. Key Requirements Candidates with extensive experience of using either computational genomic approaches or wet lab approaches to understand the molecular basis of gene networks will be considered. You should currently hold or be about to obtain a PhD in Computational, Cell, Molecular or Developmental Biology. Proven knowledge of research techniques and methodologies, evidence of a publication record in good quality publications and practical experience of applying specialist skills and techniques are also Essential Criteria. Appointment at Grade 7 is dependent upon having been awarded a PhD, if this is not the case, initially appointment will be at research assistant Grade 6B (Salary ?30,922 - ?32,607 per annum) with payment at Grade 7 being backdated to the date of final submission of the PhD thesis. Further Details A job description and person specification can be accessed at the bottom of the page. To apply for the vacancy please click on the ?Apply Now? button below. If you have any queries regarding the vacancy, please contact Prof Christopher Thompson ( christopher.thompson@ucl.ac.uk ) while questions on the application process should be addressed to Biosciences Staffing ( biosciences.staffing@ucl.ac.uk ) quoting reference number 1782567. UCL Taking Action for Equality We will consider applications to work on a part-time, flexible and job share basis wherever possible. Closing Date 2 Feb 2019 Latest time for the submission of applications 23:59 Interview date TBC Our department holds an Athena SWAN Bronze award, in recognition of our commitment to advancing gender equality. This appointment is subject to UCL Terms and Conditions of Service for Research and Support Staff. Please use these links to find out more about UCL working life including the benefits we offer and UCL Terms and Conditions related to this job. Job Description and Person Specification Apply Now
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