The Data Science Chair at JMU Würzburg as a member of the Center for AI and Data Science (CAIDAS) offers two positions for doctoral researchers (m/w/d) in the area of machine learning.
Both positions will work within the BigData@Geo2 project, the followup of the successful BigData@Geo project [1], that provides machine-learning-aided decision support for agricultural measures in the light of regional climate change. This includes prediction of crop yields and enabling proactive agricultural strategies. In the first position, you will build machine and deep learning improved climate models that provide a basis for the prediction of regional climate change and agricultural risk assessment, allowing agriculture to react in time by applying appropriate policies to deal with the challenge of changing climate-related conditions. This work focuses on the use and extension of state of the art deep learning architectures such as transformers to solve important downstream tasks such as increasing climate model resolution, identifying relevant climate indicators, integrating additional ecosystem information, and transfer function. The second position focuses on natural language processing and will allow you to work on data from many small companies in the form of historical yearbooks, as well as general information from local newspapers or social media discussing local climate events. Using this data, you will develop new methods for discovering climate, ecosystem and agriculturally relevant events that assist in the overarching goal of BigData@Geo2 of assessing the economic viability of agricultural decisions, such as which crops to grow in future seasons, or predicting crop yield. Payment is at the level of E13 according to the German federal wage agreement scheme (TV-L). Candidates are expected to have a strong background in computer science and mathematics, with a specialisation in machine learning and interest in the topic of one of the positions. Prior knowledge in the field of deep learning in one of the subject areas is advantageous. Please send your application (letter of motivation, curriculum vitae, academic records) at your earliest convenience, but no later than August 25th, 2023, to Prof. Dr. Andreas Hotho ([email protected]). You are welcome to contact us on the same address for additional details. [1] https://bigdata-at-geo.eu/ _______________________________________________ Corpora mailing list -- [email protected] https://list.elra.info/mailman3/postorius/lists/corpora.list.elra.info/ To unsubscribe send an email to [email protected]
