Good understanding of genomics, molecular biology, and technologies such as qPCR and next-generation sequencing. Research, design, and deliver training materials to effectively communicate, promote, and advance computational biology techniques and software usage by NIH researchers.

Other desirable skills include the ability to perform computational biology analyses of next-generation sequencing data and experience with various mouse cancer models. We utilize a range of techniques, including biochemical and molecular biology methods, next-generation sequencing (including single-cell sequencing), and genome editing to study these processes in cell culture, mouse models, and patient-derived models.

Responsibilities include cell culture and maintenance of human cell lines, basic molecular biology (PCR, cloning, running DNA and protein gels), flow cytometry, preparation of samples for deep sequencing, confocal microscopy, basic statistical calculations, and other duties as assigned.

Informed interpretation of experimental data and planning for subsequent experiments Bachelor's (University) degree in biology, chemistry, biochemistry or microbiology and research laboratory with documented research laboratory experience (1 academic year outside of coursework) in cell culture sterile technique, molecular cloning, genetics, and proteomics.

The ideal candidate should have:A PhD and extensive post-PhD experience in bioinformatics, computational biology, and data science. A strong CV that includes high-profile publications in the field of computational biology, cancer genomics, and/or single-cell genomics.

Familiarity with next-generation sequence data analysis tools● Basic understanding of molecular biology and next generation sequencing is highly preferred● Familiarity with single cell data analysis is preferred, but not required.

Oncology-focused computational biology research experience. A degree in Computational Biology, Bioinformatics, Immunology, or a related field. We are currently seeking an innovative, assertive and highly experienced computational biologist to assist with our Reverse Immunology efforts with primarily an oncology focus.

We are seeking an exceptional Research Associate II to join the Molecular Biology group at 10x Genomics. This is a unique multi-disciplinary position that will work closely with a variety of groups including Chemistry, Cell Biology, Computational Biology, Microfluidics, and Support groups.

Required Skills: SEQUENCING,GENOMICS,MOLECULAR BIOLOGY,QPCR,PCR, Demonstrate mastery of molecular biology methods; Demonstrated expertise in developing one or more of the following: in vitro cell-based assays, PCR-based assays; Proficient in cell culture; Ability to operate laboratory equipment independently; Experience in automation and software programing is a plus.

The Sr. Research Investigator in Computational Biology and Data Science will provide advanced analytical, bioinformatics, and machine learning support for Translational and Discovery projects in Translational Medicine.

PhD. or master's degree in bioinformatics, Computational Biology, Molecular Biology, Genetics, or a related field. This position will involve research and collaboration with scientists and engineers to develop new molecular biology products and services.

Previous industry experience is preferred and a strong background in applying computational and systems biology, including multi-omics data analyses, to research, translational and clinical programs with demonstrated ability to meet program objectives and timelines.

The ideal candidate should have an outstanding scientific reputation in the field of machine learning research for computational biology and a demonstrated passion for solving biological problems relevant to drug discovery.

A strong background in statistics, biostatistics, computer science and/or computational biology is required; and specifically, experience with analyzing high-dimensional datasets, such as whole-genome sequencing, multi-omics data, and electronic health records, is preferred.

Who You Are PhD degree in a relevant field computer science, computational biology, bioinformatics, molecular biology, cancer biology, genomics). The incumbent will apply advanced data analysis skills and machine learning in collaboration with a group of computational and biological scientists to perform translational oncology research around multimodal translational data sets for programs in clinical development.