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The role We are looking for a motivated and skilled Trait Design Scientist, ideally with a background in photosynthesis research, to drive our R&D initiatives. At Wild, we are building proprietary and "new-to-science" datasets that we use to discover new yield traits. You will play a key role in analysing these datasets and driving the future direction of data collection to accelerate this discovery work. Location We're headquartered in Milton Park, a business and technology park in Oxfordshire. This is an on-site role, though we offer flexibility and hybrid working when possible. Job requirements A PhD in a relevant discipline, e.g. Plant Science, Photosynthesis, Plant Physiology, Bioinformatics. Proven experience delivering complex scientific research projects and driving their strategic direction. Deep theoretical and practical understanding of photosynthesis; you are comfortable interpreting complex physiological data to generate biological hypotheses. Experience using gas exchange and chlorophyll fluorescence systems (e.g. LICORs, Walz), and/or other photosynthetic mechanistic studies used to dissect photosynthetic performance. A strong understanding of the genetic mechanisms that govern plant phenotypes and the factors that influence gene expression. Familiarity with Linux, bioinformatic tools, and the application of machine learning to genomic/phenotype data is highly desirable. A growth-oriented mindset focused on continuous improvement - evaluating new tools and sparking innovation within the team. Ability to distil complex data into clear hypothesis and lead collaborative decision-making sessions. Job responsibilities Lead the design and management of experiments to collect bespoke physiology and genetic datasets across diverse species. Establish robust phenotyping methods and train junior team members to ensure high-quality data collection at scale. Utilise machine learning and bioinformatic tools to mine proprietary datasets, identifying causal genetics behind key photosynthesis traits. Critically evaluate machine learning / AI outputs by integrating photosynthesis expertise with literature reviews and data from our proprietary evolutionary and cell-based platform. Lead trait design sessions, collaborating with other photosynthesis experts, construct engineers, and bioinformaticians to inform phase promotion decisions. Iteratively improve data collection protocols based on the latest photosynthesis research.