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The Chemical Biology and Proteomics (CBP) group at Biogen is seeking a creative and self-motivated Research Fellow to design, develop, and apply existing and new target identification strategies to various drug discovery programs.
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The successful candidate will be responsible for developing and implementing computational strategies to support cutting-edge research and development in the fields of protein science, antibody discovery, proteomics, systems biology, scientific databases, machine learning, and others.
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In this position, the candidate will play a crucial role in advancing our understanding of the fundamental mechanisms underlying human liver diseases through the application of state-of-the-art genomics technology, particularly single-cell RNA sequencing and spatial transcriptomics and/or proteomics.
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Working closely with Associate Professor Jessica Lasky-Su, and Research Operations Manager will be responsible for integrating multi-omic data (genomics, epigenetics, proteomics, transcriptomics, metabolomics, electronic health record data) from both clinical data and research population, using advanced computational methods such as deep learning.
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Preferred : Experience with proteomics, mass spectrometry, TAC-seq, and/or Hi-C. Foray Bioscience is unlocking biomanufacturing for plant-based industries to protect and restore natural ecosystems.
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Design and apply computational methods to analyze, integrate, visualize, and interpret bulk and single cell readouts (scRNSeq, snRNSeq, CyTOF), proteomics, metabolomics, epigenomics, and spatial tissue profiling datasets.
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We are seeking a highly motivated individual passionate about cutting-edge technology to explore single cell multiplex spatial proteomics. Analytical Skill, Analytical Skill, Analytical Thinking, Chemical Biology, Chemistry, Clinical Trials, Collaboration, Communication Skills, Curiosity, Data, Data Analysis, Design Of Experiments, Detail-Oriented, Drug Development, Drug Discovery, Ethics, Gene Therapy, Immunology, Inventory Management, Laboratory, Lifesciences, Machine Learning (Ml), Management, Medical Research, Molecular Biology {+ 10 more.
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Our group studies the pathobiology of myelodysplastic syndromes and myeloid malignancies, using a combination of quantitative proteomics, genetic and chemical screens, protein biochemistry, and cell-based assays.
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Monte Rosa’s QuEEN™ (Quantitative and Engineered Elimination of Neosubstrates) discovery engine combines AI-guided chemistry, diverse chemical libraries, structural biology, and proteomics to identify degradable protein targets and rationally design MGDs with unprecedented selectivity.
$110,000 a yearFull-timeExpandUpdated 30 days ago - UpvoteDownvoteShare Job
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3+ years of experience in MS-based proteomics; significant experience with MS, HPLC, peptide, and protein separation. Helps to produce and isolates samples for proteomics studies using cell culture techniques, immunoprecipitation, subcellular fractionation methods and protein sample preparation from tissues and/or biofluids.
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Experience in complex molecular data integration, such as transcriptomics, proteomics, and metabolomics, and in deriving insights from such analyses will be advantageous. Advantageous to have experience in complex molecular data integration, such as transcriptomics, proteomics, and metabolomics.
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Develop and implement computational strategies to analyze and integrate multi-omics data, including genomics, transcriptomics, proteomics, and metabolomics. , proteomics (MS-based, single cell proteomics, phosphor-proteomics, etc.
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Design and apply machine learning algorithms and statistics models on complex molecular data, including genomics, metabolomics and proteomics data for research purposes. Design and apply machine learning algorithms and statistics models on complex molecular data, including genomics, metabolomics and proteomics data for research purposes.
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Summary We are seeking a highly motivated individual passionate about cutting-edge technology to explore single cell multiplex spatial proteomics. Possess deep knowledge and expertise in immunology, biology, and multi-omics applications in translational research across various disease areas such as oncology (ONC), immuno-oncology (IO), immunity-driven diseases, and related treatment strategies.
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This includes data from genomics, proteomics, metabolomics, and other biological sources. + Hands-on experience in handling, processing, integrating, and analyzing large heterogenous biological data sets related to industrial drug discovery research (e.g., sc/snRNAseq, ATAC-seq, genomics, proteomics, etc.
$166,500 a yearFull-timeExpandApply NowActive JobUpdated Today
proteomics job in Boston, MA
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