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working with large datasets, including spatial information, hydrologic data and survey records. Skills and Experience To be considered for this position, you will have: completed a PhD or equivalent
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group; a multi-sectoral team of researchers, data analysts and project specialists working on producing data on population distributions and characteristics at high spatial resolution. We are looking
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a suit of fast electronics (FPGA) that will allow the following achievements: 1) To rapidly repeat single-particle experimental dynamical trajectories to gain sufficient counting statistics in order
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of priority elasmobranch species in the study area, while managing and analysing large telemetry datasets, and integrating environmental/spatial data to address key research questions on species ecology and
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distributions and characteristics at high spatial resolution. We are looking for an experienced, self-motivated, and dynamic researcher with a track-record working and publishing in the field of evidence-informed
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cooperation with the supervisor. Qualifications Required qualifications: A master’s degree or equivalent in ecology Experience with GIS, spatial statistics and modelling Programming experience: R and/or Python
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approaches including flow cytometry, spatial proteomics, transcriptomics, confocal microscopy and biochemical assays. Utilize mouse models and patient-derived samples to explore how genetic and dietary factors
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and biosensors to probe the biochemical and biophysical underpinnings of development cellular processes with high spatial and temporal resolution. We are seeking candidates with interests in
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, managing and analysing data, and publishing and presenting results. Focus will be on projects involving diagnosis, prognosis, and patient stratification based on bulk, spatial and single cell omics data
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with a PhD in computer science or bioinformatics are encouraged to apply. We create statistical, machine learning, and deep learning approaches for the processing of this data, with a major focus on