Description:
As an active team member of the Computational Biology and Digital Sciences (CBDS) at Boehringer-Ingelheim, the successful candidate will contribute to oncology drug discovery research through in silico data driven approaches. You will leverage multi-modal omics data analysis and collaborate with biologists to solve scientific challenges to advance drug discovery programs.
Duties and responsibilities:
- Strong scientific understanding and experience in bioinformatics analysis and their implications in disease biology
- Working knowledge of NGS based omics data analysis (bulk and single cell RNA-seq, spatial transcriptomics analysis is a plus)
- Identify and process publicly available and internal generated bulk, single-cell and spatial transcriptome datasets using statistical and bioinformatics techniques to create meaningful biological insights
- Apply and develop innovative analysis approaches when standard methods are not adequate
- Follow relevant scientific literature to ensure use of optimal methods and understand emerging practices across the field
- Interpret and present analysis results to coworkers, biologists and collaborators. Communicate work effectively orally and in writing
- Ensure FAIR data analysis with clear documentation and reproducibility
- Report and treat data with a high level of integrity and ethics
- Comply with applicable regulations; Maintain proper records in accordance with SOPs and policies
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- Programming experience with two or more programming languages including: Python, R for bioinformatic data analysis, shell/bash programming in unix-like systems.
- Proficiency in working with bulk and single cell NGS data, spatial transcriptomic data analysis is a plus
- Proficiency in working with cloud computing and high performing clusters (HPC)
- Experience in biological pathway analysis
- Experience in applying machine learning and artificial intelligence methods to biological data, deep learning and graph learning is a plus
- Two years hand on experience of bioinformatic data analysis
- Solid background in basic biology and disease biology. Knowledge in oncology or immunology is a plus.
- Ability to develop and benchmark machine learning algorithms
- Experience in using common public oncology datasets is a plus (TCGA, GTEX, Human cell atlas, CZ CELLxGene Discover, Human tumor atlas network, etc)
PhD/Master’s degree from an accredited institution with experience in a related scientific discipline (Computational Biology, Genomics, Biostatistics, Bioinformatics and Biological Sciences preferred)
This is the pay range that Magnit reasonably expects to pay someone for this position is
$40.00/hour - $53.00/hour.
Benefits: Medical, Dental, Vision, 401K (provided minimum eligibility hours are met).