4815398 Postdoctoral Fellow, Rare Disease Research Unit
The Integrative Biology group in Pfizer’s Rare Disease Research Unit is seeking an outstanding postdoctoral researcher to lead computational genetic analyses into modifiers of rare cardiomyopathies. This is an exciting opportunity to dig deep into human genetic and clinical heterogeneity, connect molecular and phenotypic information using large biobanks, explore and develop hypotheses, and interpret insights in support of novel discovery and translational research.
We are highly supportive and collaborative group, and the successful candidate will interact closely with internal and academic experts in genetics, bioinformatics, statistics, clinical, and laboratory research.
We are looking for candidates with a research background in at least two of: rare disease genetics, cardiovascular disease/cardiomyopathy, complex genetic analysis (e.g. GWAS, polygenic risk scores), biostatistics, electronic health records analysis, or related areas. This project is ideally suited for a candidate looking to expand their interdisciplinary skills.
- Develop, apply, and interpret genetic and statistical models using good quantitative judgement
- Effectively communicate the advantages and limitations of developed algorithms, approaches, and available data to audiences with diverse backgrounds. Interpret and describe findings at internal and external events.
- Use technical expertise to identify, extract, annotate, and integrate relevant information from large-scale genetic (WES, WGS, genotyping array) and structured clinical data sets.
- Proactively identify new research directions and testable hypotheses, taking full advantage of Pfizer knowledge and resources.
- Recent PhD in genetics, bioinformatics, molecular biology, cardiovascular biology, biostatistics, or a related quantitative field with a strong publication record. A minimum of 1 high quality first-author publications is required.
- 3+ years’ experience working in a computational environment, conducting ‘omics data analysis and using quantitative approaches to solve biological problems. Demonstrated strong quantitative experimental design.
- Excellent verbal and written communication skills. Ability to quickly master new concepts and techniques
- Ability to run standard scripts and workflows in R, Python, and/or other biocomputational programming
- Strong curiosity about human biology and variation
- Direct experience in rare disease and rare variant genetics, including prediction and interpretation of variants as disease-associated
- 2+ years’ experience working in biobanks, for example, UKBB, FinnGen, institutional resources, or others
- Working experience with disease modifiers in humans or animal models
- In-depth knowledge of public genetic databases, resources, and bioinformatic tools used for these data analyses
- Extensive experience in programming, scripting, querying or statistical analysis languages such as R, python, Perl, SQL, Nextflow. Experience with high performance computing.