A brief summary of my education and skills.


  • 2018 - 2023
    PhD Neuroscience
    University of Edinburgh
    • Thesis title - Visuomotor learning impairments in Rett syndrome.
    • Supervised by Prof Ian Duguid.
    • Thesis committee - Prof Peter Kind, Prof Stuart Cobb & Prof Nathalie Rochefort.
  • 2015 - 2018
    BSc (Hons) Neuroscience
    University of Edinburgh
    • First class honours.
    • Dissertation - A model-driven approach to understanding language processing.
    • Supervised by Dr Cyril Pernet.


  • 2023 - now
    Postdoctoral Research Fellow, Duguid Lab
    University of Edinburgh
    • Imaging macroscopic cortical dynamics to understand sensorimotor dysfunction and recovery in a mouse model of Rett Syndrome.
    • Funded by the SIDB & the MRC.
  • 2018 - 2023
    Tutor, Biomedical Teaching Organisation
    University of Edinburgh
    • Statistical and data analysis teaching for Biomedical BSc and MSc courses (R & SPSS).
    • Teaching assistant for the Neuroscience BSc programme.
  • 2017 - 2018
    Teaching Assistant, Digital Skills & Training, Information Services
    University of Edinburgh
    • Unix shell programming.
  • 2016 - 2018
    Unix Systems Administrator, Enterprise Unix Platforms, Information Services
    University of Edinburgh
    • Infrastructure automation, service delivery and user experience on a VMWare-based virtual estate.
    • Developed a web-based billing system for virtual machines.
    • Developed a platform for managing Openstack projects & instances.
    • Administration & triage of a large Linux estate.

Awards & Scholarships

  • 2023
    • Alison Douglas prize for best PhD thesis, CDBS, University of Edinburgh
  • 2018
    • Principal's Career Development scholarship, University of Edinburgh
    • PhD studentship, Simons Initiative for the Developing Brain
    • SEOTY Award for Commercial Impact, University of Edinburgh
  • 2017
    • The Edinburgh Award (Work Experience), University of Edinburgh
  • 2011
    • Fulbright bicommunal youth leadership programme (CASP) at the School for International Training (VT), Fulbright Commission, USA

Roles & Responsibilities

  • 2018 - now
    Elected member of the Senatus Academicus
    University of Edinburgh
    • Non-professorial member of the Academic Senate representing postdoctoral researchers, tutors and demonstrators in the College of Medicine and Veterinary Medicine.
  • 2019 - 2023
    Postgraduate Lead, CDBS Executive Committee
    University of Edinburgh
    • Represented PhD students in the department's senior decision-making body.

Laboratory Skills

  • Surgical skills.
    • Stereotaxic implantation of headplates for chronic single-photon mesoscale calcium imaging in mice.
  • Neurophysiology.
    • Chronic mesoscale calcium imaging recordings in mice.
    • Genetic manipulation experiments with multiple transgenic lines.
    • Chemogenetic manipulations in mice.
  • Animal behaviour.
    • Freely-moving. During my PhD, I developed a touchscreen-based forelimb reaching assay to study visuomotor learning, described in Eleftheriou et al. 2023.
    • Head-restraint. I developed a head-restraint version of the visual discrimination paradigm based on Visiomode to study visuomotor learning, which I integrated with mesoscale calcium imaging of the dorsal cortex.
  • Histology.
    • Analysis of histological datasets in 2D (fluorescent microscopy) and 3D (lightsheet microscopy), including registration, segmentation and quantification.

Programming Skills

  • Programming languages.
    • Python. I have been using Python in a professional capacity since 2013 for software engineering, data analysis and systems administration / DevOps projects. I am fluent in the language and have a delivered a variety of applications and data analysis projects over the past decade, both as part of a team and as a solo developer.
    • JavaScript. I have been using JavaScript since 2016 for building web application front-ends (initially for customer-facing web apps at UoE IS and later for Visiomode) as well as for interactive data visualisations during my PhD and postdoc.
    • C. I originally picked up C in 2016 during my time as a Unix Systems Administrator for writing and maintaining small Unix tools. My main use of C since has mainly been to speed up Python data processing where appropriate (mainly via Cython).
    • Bash. I have been using Bash in a professional capacity since 2016, mainly for short scripting tasks on Unix and Linux platforms.
    • C++. Since 2018, my experience with C++ has been exclusive to the Arduino platform for writing microcontroller software targetting Arduino and Teensy microcontrollers. Applications include actuators for behavioural tasks (e.g. lever & reward mechanisms), acquisition software for in vivo optical microscopy (single-photon mesoscopy) and software for integrating optical imaging and manipulation in vivo.
    • MATLAB. I have used MATLAB for the analysis of fMRI data during my project with Dr Cyril Pernet (2017-2018), mainly using the Statistical Parametric Mapping (SPM) package.
    • R. Between 2019 and 2022, I assisted in the delivery of undergraduate and postgraduate courses in biomedical statistics as a tutor, which included hands-on practical exercises and assessments in R.
    • C#. In 2012, I wrote a patient management application for the polysomnography department of the Paphos General Hospital in Cyprus using C#.NET, WPF and Microsoft SQL.
  • Data analysis.
    • Time series analysis & behavioural modelling. Analysis of calcium imaging (mesoscale & 2-photon) and behavioural datasets using linear regression and mixed-effects models. Contributed to Currie et al. 2022 and Dacre et al. 2021.
    • Neural decoding. Using logistic regression and Linear Discriminant Analysis to explore neural representations of actions and stimuli in mesoscale and 2-photon calcium imaging datasets.
    • Network analysis. Graph analysis of functional connectivity networks in fMRI as well as mesoscale and 2-photon calcium imaging data. Contributed to Currie et al. 2022.
    • Information theory. Using information theory metrics to track the evolution of inter-areal cortical dynamics across learning.
    • Bootstrap & resampling statistics. Powerful alternative to conventional statistics, particularly for dealing with limitations commonly encountered in neuroscientific datasets. Contributed to Currie et al. 2022 and Dacre et al. 2021.
    • Data visualisation. Experience with many of the data visualisation packages in Python, such as Matplotlib, Seaborn, Bokeh and Holoviews, for communicating results of complex imaging and behavioural analyses. Experienced with interactive visualisation libraries in Python (Holoviews) and Javascript (D3). Contributed to Currie et al. 2022.
    • Data curation. In my current role I am responsible for the curation and storage infrastructure supporting the lab's data, which span single-cell imaging to high-density silicone probe recordings. I am currently working on integrating all acquired datasets to the Neurodata Without Borders format to ease the sharing our data with the public and enhance synergy across different projects in the lab.
  • Software engineering.
    • Version control. Proficient with Git & experienced with Subversion. Routine use of Github for private and public repositories, including pull requests and code reviews.
    • Testing. Experienced with language-specific testing suites such as pytest, nose and CTest, as well as the behaviour-driven development testing framework Cucumber.
    • CI/CD. Continuous integration with Github Actions, Travis & CircleCI.
  • Systems administration & DevOps.
    • Unix/Linux. I have been using Linux in a professional capacity since 2016, with experience in the management and triage of Linux and Unix platforms at scale.
    • Virtualisation. Experience with VMWare-based enterprise virtualisation solutions such as VMWare vSphere and VMWare-integrated Openstack (VIO).
    • Automation. Experience with Puppet and Ansible for automation of Linux and Unix platforms at scale.
    • Storage. Experience with the management of a Dell PowerVault-based storage solution for scientific data since 2019, which I set up during my PhD in Ian Duguid's lab.
    • Data analysis infrastructure. Experience with the management of a virtual desktop infrastructure (VDI) solution for the analysis scientific data since 2019, which I set up during my PhD in Ian Duguid's lab. In addition to VDI, the infrastructure supports collaborative notebook-based analysis via Jupyter lab and GPU-accelerated machine learning pipelines on NVIDIA hardware.

Open Source Projects

  • 2019-now
    • A touchscreen-based visuomotor behaviour platform for rodents