Job Description We are looking for a post-doctoral researcher to join the statistical methodology and consulting group in GDD / Biostatistics, bringing expertise in two or more of the following areas: Computational biology and statistical genetics, applied data science and large-scale / "big data" computation, statistical and machine learning / deep learning. This position provides a great opportunity to join on-going and future industry/academic collaborations, as well as to interact with and contribute to data science initiatives in Novartis with the goal of demonstrating how new methodologies and data sources (such as genetic / omics data, imaging, time series, ...) can be brought together to gain new insights to guide drug development.
Your responsibilities:
Successful candidates will work in a multi-disciplinary team of statisticians, clinicians and data scientists on projects to: characterize disease progression and treatment response by integrating large clinical trial and biological datasets, demonstrate how incorporating and collecting data types such as clinical genomics or imaging add value in a drug development setting, develop new methodologies for machine learning and data analysis / bioinformatics which can be applied in a drug development setting.
Start date: asap Duration: 1-2 years
Minimum requirementsWhat you'll bring to the role:
• PhD in a quantitative / computational science (e.g. bioinformatics, machine learning, statistics, physics, mathematics, ...) • English written and spoken
Required technical and scientific skills should include:
• Strong experience with Python for data analysis (scikit-learn, numpy, Tensorflow/similar) • Experience with R for data analysis (tidyverse, mlr, ...) • Experience with computational environments for large-scale data science (e.g. high-performance computing or Spark), reproducible data science (notebooks, git/versioning, …)
Additional scientific skills in one or more of the following areas are highly desirable:
• Statistical and machine learning, and / or applied deep learning methods for time series data or images. • Bioinformatics (around DNA / RNA / proteomics data analysis) and/or statistical genetics Algorithms and methods for the analysis of ‘omics datasets (e.g. WGS / RNA-seq / …)
Why consider Novartis:
750 million. That's how many lives our products touch. And while we're proud of that, in this world of digital and technological transformation, we must also ask ourselves this: how can we continue to improve and extend even more people's live ?
We believe the answers are found when curious, courageous and collaborative people like you are empowered to as new questions, make bolder decisions and take smarter risks.
We are Novartis. Join us and help reimagine medicine.
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