Job Skills: Machine Learning
The Plant Pathology department is seeking to hire a Postdoctoral Fellow for Dr. Jesse Poland's lab. This person will be expected to independently design and implement complex genomics research experiments using the latest statistical modeling and machine learning approaches. [More]
This is a critical position in a new oncogenomics reserach group. It offers a chance to contribute to major new understanding in the patterns of mutations seen across a collection of over 100,000 tumors to better understand pathways of oncogenesis, to publish the results and see their impact on drug development. This is an ambitious project that will suit someone who wants to tackle a major challenge and make a major mark on cancer biology. [More]
The Department of Computational Medicine and Bioinformatics (DCM&B) at the University of Michigan Medical School seeks outstanding applicants for tenure-track and tenured faculty positions in computational medicine and bioinformatics. This is a faculty position at the Associate Professor level. [More]
KPMG is currently seeking a Data Scientist, to join us in any major US city with a KPMG office. Responsibilities: Analyze and model structured data using advanced statistical methods and implement algorithms and software needed to perform analyses; Build recommendation engines, spam classifiers, sentiment analyzers and classifiers for unstructured and semi-structured data; Cluster large amount of user generated content and process data in large-scale environments using Amazon EC2, Storm, Hadoop and Spark; Perform machine learning, natural language, and statistical analysis methods, such as classification, collaborative filtering, [More]
Unique opportunity to join an interdisciplinary team bridging the Harvard Medical School, the Massachusetts General Hospital, and the Broad Institute of Harvard and MIT. The Lawrence Lab at the Massachusetts General Hospital Cancer Center seeks well-qualified candidates to join a team of computational biologists working at the forefront of cancer research and treatment. We use computation as a powerful microscope to study both the fundamental biology of cancer initiation and progression, as well the diagnosis and treatment of cancer patients in the hospital setting. [More]
We are seeking a colleague with extensive training and experience in computational biology, statistics, and population genetics to join our highly productive, world-class Ancestry Research & Development team. Our team both develops novel algorithms to interpret the data of individual 23andMe customers and analyzes data from over 1 million customers in order to publish novel findings regarding human genetics and history. We are seeking a team member who is excited to develop cutting edge features that will reach millions of people. [More]
We are looking to recruit an enthusiastic, highly motivated Bioinformatician to work in the EGA and Archive Infrastructure Team at the European Bioinformatics Institute (EBI) located on the Wellcome Trust Genome Campus near Cambridge in the UK. The successful applicant will work with a focused team of developers, biologists and user support personnel to provide a world leading reference genetic variation resource as part of the European Genome-phenome Archive (EGA) project. You will engage in both internal and external (national and international) collaborations, especially the RD-Connect consortium (www.rd-connect.eu) and will have the opportunity to gain expertise in biological ontologies, metadata and scientific data modelling primarily related to research into rare disease. [More]
The successful applicant will take a lead role in analysing Whole Genome, RNASeq and Bi-sulphate Sequencing data generated in collaboration with the Wellcome Trust Sanger Institute and Babraham Institute, to identify and predict potential relationships between genetic and epigenetic changes which occur during the long term maintenance of PSCs under the supervision of Professor Peter Andrews and Dr Marta Milo. [More]
The Bioinformatician will provide bioinformatics expertise and support for metagenomic sequence analysis, including benchmarking and evaluation of different free and open source (F/OSS) and Commercial off the Shelf (CotS) software products for pathogen genomics, metagenomics and metatranscriptomics. [More]
A PhD position is available in developing and applying computational and machine learning models for multilayered trans-omics data sets generated by state-of-the-art mass spectrometer (MS) and next generation sequencer (NGS). Our research project, funded by the Australian Research Council (ARC), aims to develop novel machine learning algorithms to analyse and integrate large-scale MS-based omics data with ultra-fast NGS-based omics data generated from complex biological systems. [More]