Experience

Research Associate in Responsible Research and Innovation - University of Manchester: 2019 -

Research Project Manager - University of Manchester: 2012 - 2015

Qualifications

PhD in Science and Technology Studies - University of Edinburgh: 2014 - 2019.

MSc. (Research Methods) in History of Science, Technology, and Medicine - University of Manchester: 2013 - 2014. Merit.

BA (Hons) English - Manchester Metropolitan University: 2009 - 2012. First Class.

Awards and Funding

EPSRC funding for doctoral research: 2014 - 2018

Research Activities

Linked research interests with the ERC funded project: 'Engineering Life: Ideas, Practices, and Promises'

Chris Mellingwood has not added any teaching activity to this section yet.

PhD Title

Amphibious Researchers: working with laboratory automation in synthetic biology

PhD Supervisors

PhD Overview

My PhD analyses the use of robots and automation in academic biosciences laboratories in the UK. Both system vendors and policymakers argue that robots, specifically liquid-handlers and robotic arms, offer more efficient, precise and reliable methods for experimental work. These arguments for the potential of automation systems for the biosciences form a cadre of promissory narratives about the future value of such technologies. One reason vendors promote the use of robots is to remove error-prone humans, with their need for sustenance and sleep, offering instead the mechanical reliability of a robot system unencumbered by such bodily limitations. Somewhat paradoxically, I argue that to negotiate the hybrid disciplinary space of laboratory automation and the biosciences, researchers need significant embodied skills. Furthermore, they must forge relationships among multiple knowledge communities, and engage in boundary-work to manage ambivalences and deal with competing demands. Laboratory-based automation system users learn how to be skilled in embodied ‘fingertip-feeling,’ and how to be adept at relationship management and boundary-work. To do this, they need to understand both ‘wet’ cell behaviour and ‘dry’ robot behaviour; they must become amphibious researchers.

My study identifies five promissory narratives found in policy documents and system vendor descriptions of laboratory automation and the biosciences, particularly in automation-driven synthetic biology. These promissory narratives describe potential future benefits of increasing automation in biosciences laboratories. The five narratives are that automation will: result in more time for researchers because robots are more efficient and more precise; increase parameters and the ability to tackle problems with very large numbers of variables; enhance the reproducibility of experimental results; provide increased technological capacity for laboratories, making them more competitive in international funding arenas; and result in further opportunities for commercialisation of products and services.

Through an analysis of documents, interviews and laboratory practices, I show that these promissory narratives for automation and the biosciences are reconfigured by the lived experiences of laboratory users. I establish that researchers’ lived experiences can both challenge and support promissory narratives in this area, and argue that developing understanding of users’ practices is essential to an assessment of the future value of automation-driven synthetic biology. My thesis further demonstrates that the ways that researchers make automation systems work in the biosciences involve an attentive engagement between users’ bodies, their competences, and their belonging and identity as part of particular groups. Researchers using laboratory automation technologies engage their bodies and manage their relationships to generate trust and confidence in robot functioning. These researchers have to mobilise the ‘wet’ and the ‘dry’ simultaneously to maintain a proper functioning system. In short, they must be amphibious researchers.

Mellingwood, C. (2018) 'Data Science for Experimental Design Workshop', The Turing Institute, 17th October 2018.
Session lead: What are the obstacles to integrating data-driven experimental design in real laboratories, from an ethnographic and sociological perspective?  (https://datascienceforexperimentaldesign.github.io/)

King, RD, Schuler Costa, V, Mellingwood, C & Soldatova, LN (2018) 'Automating sciences: Philosophical and social dimensions', IEEE Technology and Society Magazine, vol. 37, no. 1, pp. 40-46  (https://ieeexplore.ieee.org/document/8307145)

Mellingwood, C. (2016) 'Envisioning experimental space through automated laboratory work' Conference paper at the Society for New and Emerging technologies (S.NET) conference, Bergen, Norway, October 2016.

Mellingwood, C. (2016) '"Not something we need to worry about": Automation in biosciences laboratories' Paper presentation at SynthSys Open Centre Meeting, University of Edinburgh, Sept. 2016.

Mellingwood, C. (2016) 'The case of robotics in UK synthetic biology: envisioning experimental space through automated laboratory work' Poster presentation at STIS Annual PhD conference, University of Edinburgh, April 2016.

Mellingwood, C. (2016) ‘Automation, expectations, and laboratory work - a robot in every lab?’ SynBio PerspectivesSynthSys opinion piece. http://www.synthsys.ed.ac.uk/news/synbio-perspectives-automation-expectations-and-laboratory-work-robot-every-lab

Mellingwood, C. (2015) 'Following the herd: paradoxes in the social study of synthetic biology' Engineering Life Project blog post. http://blogs.sps.ed.ac.uk/engineering-life/2015/12/02/following-the-herd-paradoxes-in-the-social-study-of-synthetic-biology/

Ellwood, S, Chambers, N, Llewelyn, S, Begkos, C, Wood, C. (2015) 'Debate: Achieving the benefits of patient-level costing - open book or can't look?'. Public Money and Management. 35 (1). http://dx.doi.org/10.1080/09540962.2015.986893 

Chambers, N, Llewellyn, S, Adil, M, Wood, C, Begkos, C, Ellwood, S. (2014) 'Finance. It is time to open the book on NHS finances'. Health Service Journal. 124 (6403). http://www.ncbi.nlm.nih.gov/pubmed/25174236