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therapeutic decision-making. Position Overview The successful applicant will work closely with a collaborative team to: - Identify and validate molecular biomarkers (proteomic, genomic, cellular) that predict
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for research and employees from all over the world. We are looking for a Postdoctoral Fellow in Biochemistry-Proteomics (f/m/d) (Ref 01/2026) to join the group ‘Molecular Pharmacology & Cell Biology’ led by Prof
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. The postdoctoral fellow will lead efforts to develop novel machine learning models for integrating omics datasets (e.g., genomic, transcriptomic, epigenomic, proteomic, metabolomic) with relevant molecular pathways
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candidate will use a combination of microscopy, proteomics, genetic constructs, and in vitro reconstitution to study if these change in biomass density results in phase transitions in the cytoplasm and if
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at https://postdoc.hms.harvard.edu/guidelines . With this appointment, you are represented by the Harvard Academic Workers (HAW) – UAW for purposes of collective bargaining and matters affecting your
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records at the TRUST platform (https://trustplatform.sg/) . Large-scale proteomics data have also been generated for these individuals. We are inviting a motivated Research Fellow to join our PRECISE-SG100K
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: Proteome sequencing data analysis. Implementation of analytical pipelines for RNA-seq and proteomics data validation in several samples. Legislation framework: Research Fellowship Holder Statute, in
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use proteomic data to identify novel regulators of nervous system stability in health and disease. Examples of the application of this type of workflow from the Wishart group can be found here: https
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, epigenomics, transcriptomics, and proteomics) information. The postdoctoral fellow will develop and refine machine learning methods for analyzing histopathology, clinical, and multi-omics data, collaborate with
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(proteomics, metabolomics, lipidomics) and phenotypic end-points. As our model system, we study springtails (Collembola), key terrestrial ectothermic invertebrates of the soil community. This PhD project is