Scientist/Principal Scientist, Computational Scientist (Sleep) in Edinburgh

AstronauTx is a small, agile biotech developing therapeutics to treat neurological disorders by improving sleep architecture. We operate as a semi-virtual team, emphasising collaboration, creativity, and rapid execution. Our culture values flexibility, hands-on problem-solving, and individuals willing to roll up their sleeves to drive results in a fast-moving environment.

We are seeking a motivated and technically skilled Computational Scientist to join our bioinformatics and data analysis team. This is a hands-on role: you will spend most of your time analysing sleep electrophysiology data, writing and running code, and building and improving the computational pipelines that underpin our research and translational programmes. You will work closely with the Senior Principal Scientist, Bioinformatics Lead.

This role is ideal for a scientist with a strong foundation in sleep research and quantitative analysis, who is motivated by direct technical work and keen to apply their expertise in a fast-paced biotech environment. As our programmes scale, there will be scope to grow into broader responsibilities, but the core of this role is doing great science and building robust tools.

• Sleep data analysis
  • Process, QC, and analyse sleep electrophysiology data, including EEG/PSG recordings from preclinical and clinical studies.
  • Apply sleep-specific signal processing methods, such as spectral analysis, sleep staging, event detection, cross-frequency coupling and related methods.
  • Interpret findings in the context of neuroscience and drug mechanisms, contributing to study reports and the identification of pharmacodynamic markers of sleep quality.
• Pipeline development & engineering
  • Build, maintain, and improve automated analysis pipelines for processing sleep and physiological datasets.
  • Develop reproducible, well-documented code in Python and R, with an appreciation for good software engineering practices, including version control (Git/GitHub), modular design, testing, and code review.
  • Apply engineering practices pragmatically: we prioritise engineering rigour for core, reusable functions and pipelines, and accept that pace sometimes means not everything can be built to the same standard.
  • Use workflow management tools (e.g. Nextflow) to develop robust, scalable pipelines (experience with a workflow management tool is a bonus).
  • Contribute to the integration of sleep data with other data modalities as the programme evolves.
  • Support data management, storage, and organisation to ensure analytical pipelines are reliable and well-maintained.
• Collaboration and communication
  • Work closely with the Bioinformatics Lead and cross-functional colleagues including neuroscientists, clinicians, and data scientists.
  • Present analytical findings clearly to both technical and non-technical audiences.
  • Contribute to internal reports, regulatory documents, and peer-reviewed publications as appropriate.
  • Stay current with emerging methodologies in sleep science, signal processing, and computational biology.

We are open to candidates at different career stages. What matters most is the quality and relevance of your experience, not the number of years. We anticipate the right candidate will have some post-PhD experience, whether from a postdoctoral position in a sleep or neurophysiology lab, or from a Scientist role in a relevant biotech or CRO, though exceptional candidates straight from a PhD will also be considered.

• PhD in Neuroscience, Biomedical Engineering, Computational Biology, Physiology, or a closely related field.
• Candidates with a Master’s degree and substantial relevant experience will also be considered.

• Direct, hands-on experience with sleep electrophysiology data analysis, including EEG and/or PSG data.
• Demonstrated experience working in or closely with a sleep research laboratory (academic or industry).
• Proficiency in Python and R for data analysis – we expect some comfort with both, even if one is stronger. You should be comfortable writing, debugging, and maintaining your own code.
• Experience with signal processing techniques relevant to neurophysiological data (e.g. spectral analysis, sleep staging, event detection and related methods).
• Familiarity with version control (Git) and reproducible research practices.
• Experience with workflow management tools such as Nextflow or Snakemake is advantageous.
• Experience with cloud or HPC computing environments is advantageous.

• Genuinely hands-on: you get energy from doing the analysis yourself and you take pride in clean, well-structured, reproducible work.
• Can-do attitude: willing to tackle the unglamorous parts of the role (data wrangling, pipeline debugging, documentation) with the same enthusiasm as the science.
• Deep intellectual curiosity about sleep, neuroscience, and the brain’s role in health and disease.
• Scientifically rigorous, with strong attention to detail in both data analysis and its interpretation.
• Self-directed and comfortable taking ownership of defined workstreams, while knowing when to loop in colleagues or escalate.
• Collaborative team player who thrives in small, cross-functional, semi-virtual teams.
• Clear and concise communicator, able to convey complex analytical findings to both technical and non-technical audiences.