Job Skills: Machine Learning
Applications are invited for the post of a Post-doctoral Bioinformatician to work on a collaborative translational research project between the groups of Dr Matthias Zilbauer (Department of Paediatrics at the University of Cambridge, UK), Dr. Paul Lyons (Department of Medicine, University of Cambridge, UK) and Dr. Oliver Stegle (European Bioinformatics Institute - EBI, UK). [More]
We are seeking highly motivated and enthusiastic computational individuals who will work within an interdisciplinary team comprising computational scientists, data scientists, bioinformaticians, physicians, and biomedical scientists on immune-related projects in cancer. We are currently seeking a Computational Biologist with formal background in computer science, mathematics, physics, or statistics (with experience in machine learning)... [More]
A bioinformatics/computational biology postdoctoral research position is available immediately in the laboratory of Dr. Sue Rhee at Carnegie Institution’s Plant Biology Dept (Palo Alto, CA). The main goal of the project is to develop an algorithm to predict causal genes from QTL regions in plants, particularly in the model C4 grass Setaria. [More]
The Dana-Farber Cancer Institute seeks a POSTDOCTORAL COMPUTATIONAL BIOLOGIST AND DATA SCIENTIST FELLOW, under the Van Allen lab and the Center for Cancer Precision Medicine to work on the analysis of new datasets generated in the context of multiple clinically oriented cancer sequencing projects in order help advance efforts for precision cancer medicine. [More]
We are seeking outstanding applicants for Postdoctoral positions in the Department of Bioinformatics and Computational Biology at the MD Anderson Cancer Center to develop computational methods and perform statistical analyses to interpret large-scale high-dimensional single-cell flow/mass cytometry data towards understanding the etiology and evolution of cancer. [More]
The Computational Biologist will work closely with colleagues within the Systems Immunology function as well as project teams and partner lines to inform the I&I drug discovery pipeline based on integration and analysis of omics scale datasets, e.g. RNASeq, genetics, FACS/cyTOF. The Computational Biologist will internalize (or design) and apply fit-for-purpose computational approaches to understand immune dysfunction in patients and work towards hypotheses for therapeutic mechanisms. [More]
A health care company with global reach. A product pipeline filled to the brim. A team committed to scientific advancement. Think what's possible. Novartis and its associated companies are always looking for talented employees globally We are seeking a Principal Statistical Consultant who will work in collaboration with Biostatisticians, Pharmacometricians, Global Project Teams and senior Statistical Modeling colleagues to ensure the use of state-of-the-art statistical methods, models and machine learning are used at the trial and project level. [More]
The Computational Science Initiative of Brookhaven National Laboratory is currently looking for a computational scientist with a focus on deep learning for scientific knowledge discovery. The post holder is expected to work closely with researchers at BNL, as well as collaborate with researchers at other institutions. The post holder will research and develop novel, highly scalable deep learning algorithms and applications to support scientific data analysis on various very large scientific datasets. [More]
Stanford Center for Genomics and Personalized Medicine (SCGPM), situated in the heart of SF Bay Area, has an excellent opportunity available for a motivated bioinformatician. This is a key position with bioinformatics core team that will support bioinformatics services via Genetics Bioinformatics Service Center.This position is 1 year, fixed-term, renewable based on funding. [More]
As a data scientist working with Cerner Technology Services and Enterprise Data Management you will work on challenging, top-tier problems originating from a wide spectrum of internal business and IT use cases and processes. Creativity, communication skills, a drive for learning, and flexibility towards both problem spaces and statistical methodologies characterize the successful candidate who will join this team. [More]