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Essential Job Responsibilities
• Contribute to the development of multivariate biomarkers which are
predictive of drug response using broad array of experimental data generated
internally or available from external sources. This key task will involve
judicious application of statistics and machine learning while collaborating
with other scientists.
• Build statistical models and analyse experimental data from diverse
platforms, including in vivo experiments, gene expression, miRNA profiling,
chemical assays, etc.
• Develop novel methods for leveraging data from external sources and
combining it with internally generated information using approaches such as
Semi-Supervised Learning.
• Serve as expert statistical consultant to the various departments at
the site.
Required Qualifications:
Required:
Ph.D. in Statistics, Biostatistics, Statistical Genetics or closely
related field
Solid knowledge of statistical theory and its application including
mixed effects models
Theoretical knowledge and practical experience with modern machine
learning methods as practiced in the biomedical field with particular
emphasis on “small n-large p” problems
Experience in analysing gene expression including handling raw data
, normalisation, removal of technical artefacts, and analysis of relation to
clinical/biological outcomes
Outstanding computational skills, proficiency in R and facility
with diverse computer systems
Personal traits: scientific maturity, highest level of
responsibility with careful attention to detail, easily working both
independently and under close guidance, ability to collaborate well with
scientists in other fields, flexibility in handling diverse types of
problems in the setting of industrial research
Desirable:
Experience in working with non-mRNA molecular data, such as miRNA,
CNV, RNA-seq, Mass Spectrometry or epigenomic platforms
Expertise in a leading edge technical topic such as Semi-Supervised
Learning, Manifold Learning or Bayesian statistics with “small n-large p”
problems
Experience with both pre-clinical and clinical projects
Experience in Oncology |
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