|Placement base location||This role can be fulfilled remotely. The offices are based in Harpenden, Hertfordshire.|
|Contact for enquiries||Lindsey Moran (Head of People)|
|Contact details||Email: Lindsey.firstname.lastname@example.org|
|Placement job title||Bioinformatics/Data Science Placement|
|Potential start date||Flexible to suit the candidate.|
|Potential working pattern||Daily work pattern: Mon- Fri
Total hours per week: 35 Full-Time/Part-Time: Full timeWe operate a flexible working pattern with core hours of 10am-4pm.
|Details of application method||CV and interview (can be conducted remotely). Please apply by emailing with your CV to email@example.com.|
|Application closing date||None – this is a rolling opportunity.|
|Overview of PIPS organisation|
|Phytoform Labs Ltd (Phytoform), a fast-growing AgBiotech startup located at the Rothamsted Research science park, is offering a 3-month internship for a motivated Bioinformatician. This internship is ideally suited for PhD students needing to complete their Professional Internship or PhD Students (PIPS). Phytoform focuses on sustainability in agriculture by developing new crop varieties specifically adapted to climate change challenges. Phytoform has developed a proprietary AI-enabled platform CRE.AI.TIVETM that allows for predictive genetic design and the build, test, validate cycle for crop genetics.|
The focus of this internship will be to join our fast-moving data science team that is developing large foundation models for plant genetics. The outcomes of the models are directly passed to our R&D team that validates model predictions in wetlab, creating a unique iterative loop with genetic outcomes that lead to useful crop traits.
You will have direct exposure to all elements of a cutting-edge data science project. With your background in Bioinformatics, your direct responsibility will be helping the team prepare, filter and package -omics datasets that will be used for model training. In addition, you will work to organise the data in easy to access databases with critical assessment of the data sources and data quality.
|Studying a relevant discipline.|