The research project entails the implementation and optimization of deep learning models for enhanced identification of biomolecules like peptides, proteins and metabolites from data acquired in hundreds of public and in-house liquid-chromatography mass spectrometry experiments. The candidate will use high-end deep learning methods to fully utilize the information contained in the output from these LC-MS experiments, with the aim to vastly reduce both instrument time and expenses. The application must include the following: • A letter of motivation, including details on qualifications within subject area (max. Should your referees wish to send their letters directly to us, please have them use e-mail: firstname.lastname@example.org And please note that these also need to reach us before deadline.
We are seeking outstanding candidates with strong analytical and problem-solving skills, who are strong in written and oral communication (in English) and have documented experience in machine learning (in particular deep learning) and bioinformatics. Expertise in handling and understanding protein mass spectrometry data is an advantage, but not a requirement. The successful candidate will participate in independent research projects and assist in the supervision of undergraduate students. The selected candidate will develop a proof-of-concept framework for detecting antibody-derived peptide signatures in proteomics datasets. More specifically, the research project entails the analysis of millions of B-cell receptor sequences by machine learning to determine disease-specific antibody peptides that can be detected in proteomics datasets.
This position requires a Master's degree or equivalent in Computer Science, Mathematics & Computing, or Engineering. Candidates in the final phase of their Master study may apply. A successful candidate should have a strong interest in at least one of the following topics: fundamental machine learning, neural network architecture, artificial intelligence, and interpretable learning. Since our research results are evaluated experimentally, good programming and system research skills are necessary. Applicants must document fluency of in English and be able to work in an international environment.
PURPOSE: The Devices Research and Innovation (DRI)-US Data Scientist will contribute to DRI-US vision to explore and develop new technology, product ideas, and game-changers that may hold the potential to add value to patients and Novo Nordisk in the future within therapeutic areas covered by Novo Nordisk corporate strategy. The Data Scientist will act as an expert in identifying data sources and interpretation of the right data in order to give essential input to the design of attractive products that balance satisfying user needs with innovative technical solutions and business potential according to Novo Nordisk corporate strategy. The Data Scientist will be responsible for developing, implementing and applying technical platforms. At the same time, the Data Scientist will be a strong team player, who contributes to development of device solutions and acts as a role model for others to follow. Internal relationships include R&D colleagues in DRI-US and Device R&D colleagues in Denmark.
The application and supporting documentation to be used as the basis for the assessment must be in English. Publications and other scientific work must follow the application. Please note that applications are only evaluated based on the information available on the application deadline. You should ensure that your application shows clearly how your skills and experience meet the criteria which are set out above. Please submit your application electronically via Jobbnorge website.