R Programmer

We are currently recruiting for R Programmer for a contract position. The task at hand is to build an R package to analyse human movement data derived from music performances, which will then allow the client to ingest and pre-process data, tabulate andplot summary functions, and run defined analytical functions with a range of parameter settings. Most of the advanced analytical functions already exist in other packages and this package should be CRAN-releasable.

**R Programmer**

**ASAP Start**

**9-week contract**

**Essential experience**:

- Experience as an R Programmer
- Have previously worked with Time Series Analysis, particularly advanced experience of time series analysis techniques: Granger Causality and Cross-Wavelet Transforms (CWT)
- Strong data analysis skills

**Responsibilities**:
**Stage 1**:Data Ingestion, pre-processing, and summary functions:
- Load movement and annotation data. We should be able to specify which performances to consider, which sections within those performances, which instruments, and which body parts; also specify which category of annotation to consider.
- Process movement data (normalise, interpolate missing data points, smooth/filter, detrend; flexible options with reasonable default values); optionally calculate displacement and velocity for these data points.
- Represent data as S3 or S4 objects and plot summary functions. Time series for selected body parts plotted with selected annotations, with the results of summary functions such as periodicity detection tabulated.
**Stage 2**: Granger Causality

- Using existing Granger Causality and Conditional Granger Causality functions and calculate summary measures for pairs of musicians in specified performances.
- Using the same functions, carry out windowed analysis and plot the results between specified in/out points and with visualisation of selected annotations.
**Stage 3**: Wavelet Transforms

- Calculate Wavelet Transforms, CWT energy and relative phase for pairs of data points and plot the results between specified in/out points and with visualisation of selected annotations.
**Stage 4**: Analytical Functions

- For the final analyses, meta-analytical functions answer specific questions, e.g., is a certain measure significantly higher at defined times than at other randomly chosen parts of the performance?
**Stage 5**: Completion of package to CRAN specification

Carbon60, Lorien, SRG - the Impellam Group STEM Portfolio is acting as an Employment Business in relation to this vacancy.