Rhenix Lifesciences is a boutique R&D organization focused on supporting scientific organizations within broader life sciences. We are a group of scientists with expertise across different scientific disciplines working together with a singular goal of finding solutions to improve scientific access for everyone. Our internal research is focused on bioinformatics and digital medicine. This includes leveraging data sets across different diseases, and technologies such as Artificial Intelligence (AI) and IoT to identify novel pathways that might lead to novel therapeutic opportunities. We also help organizations to streamline their clinical activities: protocol writing and scientific consulting, and to improve their digital transformation.

Job description

We at Rhenix Life Sciences are focused on personalized and precision medicine within P4 medicine framework. Wearables such as smartwatches and CGM provide a dynamic window into the health of a patient. It provides an opportunity to manage care including prescriptions and mobility and can predict clinical incidence.

We are currently looking for a scientist who can generate insights from the raw data. The candidate is expected to have hands-on experience with time series analysis, imputation and correlation. Ability to identify frequency domain components including power analysis. In addition, the candidate is expected to contribute towards a multi-omics framework with dynamic data sets including publicly available data sets. The candidate is expected to teach and mentor juniors. The candidate will have an opportunity to contribute towards developing bioinformatics pipelines for personalized cancer vaccines.

An ideal candidate should have a degree in physics, data science or other related fields. Hands on

experience with Python and R are mandatory. A first author peer-reviewed publication in the relevant field is important. Excellent command over Linux environment. Significant experience with programming languages such as R and Python. Ability to carry out data analysis in local systems, high performance cluster and cloud environment. Familiarity with data analysis for imputation, identifying data patterns and prediction of health or disease status or adverse events is required.

Experience in application of machine learning methods to derive meaningful insights from wearable health devices data using ML is a must and must be exemplified by at least one research publication (Review article will not be considered).

Ability to manage and perform reproducible data analysis using workflow management systems

Location: Remote working

Salary: 50K

Must have skills:

R/Python programming

Machine learning

Digital health data analysis

At least one research publication using digital health data analysis