Jobs at Lifelines Neuro

In this role, you would be reporting to the Head of Research and Development and Chief Scientific Officer. You would be focused on adapting, elaborating, and automating processing pipelines. You would be working directly with an electrical engineer and neuroscientist to build software that is high quality, efficient, accessible, and extensible. Ideally, with a strong understanding of electrical engineering and signal processing and the needs of both our clients and (internal) end-users, you will bridge the gap between research and production-level software.

● To generate limited scope project specifications with possibilities for elaboration of a data processing pipeline for pharmacokinetic/pharmacodynamic analyses and possibly more.

● To adapt from existing code, build, and maintain R (or other pervasive open source) packages geared towards analyses of clinical trials EEG data.

● To build high-quality, composable tooling that enables researchers to analyze clinical trials data asynchronously and in (near) real time.

● To automate data analysis and reporting, for both internal (e.g. scientists, executives) and external audiences (e.g. pharma, CROs).

● To collaborate closely to understand workflow pain-points and inefficiencies that can be resolved with better tooling and processes.

● To develop tooling for efficient dataset curation, versioning, and access to enable reproducible research.

● To generate generalizable data visualisation and plotting tooling to speed interpretation of results

● Minimum of one year of hands-on experience in developing production-level software for research purposes.

● Solid knowledge in signal processing, statistics, and optimization.

● Demonstrated experience in crafting efficient, maintainable, and composable packages in R or other pervasive open source software.

● Enthusiasm for working with extensive time series biosignal data, such as EEG, with previous experience preferred.

● Comfort building cloud infrastructure tailored for the analysis of substantial datasets.

● Excellent verbal, written, and presentation skills.

● Ease working within a highly asynchronous hybrid environment, with a track record of successful past experiences.

● Experience levels ranging from Master's degree with 3-7 years, doctoral degree with 3-5 years, or equivalent comparable experience..