Jobs at Genetwister

Appropriate experimental design and data analysis of breeding trials are essential. Genetwister offers assistance in the experimental design, taking into account all practical considerations of the breeding program.

To interconnect different knowledge domains, we use different semantic web technologies.

With increasing sample numbers comes the need for automating the most valuable and most often applied protocols at Genetwister.

With increasing sample numbers and marker panel sizes, it is valuable to increase the throughput of sequencing and genotyping procedures. Genetwister develops cost-effective methods and applies available methods for allowing high-throughput genomics.

Discovery of markers in all plant species by next-generation sequencing for accelerated plant breeding

Genomic selection (GS) accelerates achieving genetic gain through shorter breeding cycles and is an alternative to marker-assisted selection. Genetwister implements new breeding schemes and methods that integrate GS for crop improvement.

Genetwister investigates new precision phenotyping methods to integrate phenotypic data into genetic models to support breeding

At Genetwister, tools are developed using distributed computing models and technologies like Spark and Hadoop.

High performance BLAST implementation adapted to run in Spark clusters.

Advanced statistical models are needed to increase the power to discover (new) associations between genetic and phenotypic variation.