Official File: Biotech Data Scientist Postdoc – Job Posting
The Kuhn-Hicks laboratory at USC is a leader in mathematical oncology for predictive mapping of cancer progression and treatment response. The laboratory uses clinical, demographic, and single cell morpho-proteo-genomic data to build predictive models to aid in improving patient care and outcomes.
Our rapidly growing team is looking for a postdoctoral fellow with expertise in data science to apply machine learning concepts to analyze clinical, liquid biopsy, and real-world evidence data sets. A successful candidate will have the determination to improve outcomes for cancer patients and discover novels ways of applying data simulation, machine learning, computational and analytical skills to complex data sets.
- Research, design, implement and evaluate machine learning algorithms and statistical models for clinical datasets
- Identify technical challenges, define requirements and prioritize efforts to meet deadlines of the internal team and external collaborators
- Assist with defining requirements and architectures for next-generation machine learning / statistical analysis products
- Develop model and algorithms, perform exploratory research, and collaborate with engineers as well as fellow data scientists to implement your solutions as products.
- Apply machine learning to build prediction models for cancer treatment and side effects
Ph.D. in Computer Science, Engineering, Mathematics, or equivalent.
Skills and Expertise
- Minimum 5 years of programming experience
- Experience in the field of data science/data analytics, mathematics, or bioinformatics
- Strong written and verbal communication skills
- Experience in building models and developing algorithms for machine learning, statistics, optimization, and/or simulation
- Experience in SQL, Python, and R
Work is in a typical office environment.
Applicants should contact Prof. Peter Kuhn at email@example.com.