Biomedical Research Engineer
At the Stanford Center for Genomics and Personalized Medicine (SCGPM), we are applying our expertise on the science and ethics of genomics to build a new collaborative model of science focused on transforming the practice of medicine. This creates a new paradigm of patient¬-centered medicine that can monitor the entire genome of individuals to vastly improve disease prediction, prevention, and treatment of conditions such as cancer, diabetes, heart disease, asthma, schizophrenia, and many others. Stanford is uniquely positioned to drive such an endeavor. We have extraordinary talent in science, engineering and medicine; our location in Silicon Valley provides unique opportunities for technological collaborations; our faculty are highly successful at obtaining competitive funding for their research; and we are leaders in the ethics of personalized medicine and in training physicians to help patients understand their genetic information. Genomics, in particular, requires technologically advanced facilities and computational infrastructure and benefits from an economy of scale that can only be achieved in center settings like the SCGPM. Our Center offers an omics driven biomedical platform composed of state¬of¬the¬art laboratory and computational facilities to an interdisciplinary research community.
Our computational facility is built on the principles of NIH Data Commons ¬ a platform where researchers have access to secure, scalable, affordable, and flexible computing environments, software tools, reference data and specialized bioinformatics consulting. Our bioinformatics core team works on multiple high-value projects and in the process develops this Commons. The Commons in turn is available to all Stanford researchers, our affiliates (e.g. Stanford Hospitals, VA) and collaborators at other institutions. Our core team is interdisciplinary and has a wide range of expertise and diversity of experience. What is common is that they are all exceptionally talented individuals with a passion to make a difference.
We are seeking a Biomedical Research Engineer to join our core bioinformatics team. Our team works closely with faculty members, researchers, and technologists to build data science research infrastructure solutions. Suitable candidates will have a fundamental understanding of Big Data-scale programming, including distributed programming, Cloud programming, and coarse- and fine-grained parallelism. Experience with programming methodologies like Spark and Hadoop are plusses. Data Science skills are needed – you will be expected to use the solutions you build.
All our solutions, while technologically broad, support biomedical research. It is critical to be able to communicate effortlessly with the biomedical community who are working with data types such as Next Generation Sequencing (DNA¬-Seq, RNA¬-Seq), Imaging (e.g. MRI), biosensors (e.g. wearable devices) and methods such as Genome Wide Association Studies (GWAS), Machine Learning (e.g. Clustering), and algorithms (e.g. Decision Tree, Bayesian Classifiers). You are expected to be comfortable with complex algorithmic concepts of alignment, variant calling, and gene expression analysis.
Our systems support bleeding-edge academic research. We build for real time data analysis at affordable prices for Big Data. We build for reproducible science. We build for community adoption. These requirements are challenging. We do not expect anyone to know everything at the get-go – Stanford is a learning environment. But we do expect everyone in the team to be fast learners. We have a lean team; this means that you own your project from conception to user support. For you to be effective, you need to be analytically strong, be an exceptionally strong individual contributor, a trusted collaborator with strong work ethics, and be a strong communicator.
This is a 3 Year Fixed Term
- Conceptualize design, implement, and develop solutions for complex system/programs independently. The team typically develops novel biomedical applications based on open source or commonly accessible technologies. These applications can be large in scale, involving very massive datasets (Terabyte- to Petabyte-scale), thousands to millions of experiments, multiple researchers (1¬100s), institutions (1¬20), and they support various regulatory requirements.
- Work with a variety of users to gain information, and develop intra¬system tradeoffs between different users, as necessary; interact with a diverse client base and outside vendor contacts.
- At any time, the team routinely works with dozens of clients including Stanford faculty, collaborators, graduate students and postdoctoral scholars, startups and mature companies.
- Document system builds and application configurations; maintain and update documentation as needed. These applications are used in innovative and cutting edge research and related publications and reproducibility and traceability are integral to deliverables.
- Provide technical analysis, design, development, conversion, and implementation work. We expect our team members to own the project in its entirety.
- Work as a project leader, as needed, for projects of moderate complexity. Nearly all projects involve multiple stakeholders, timelines are often tight and it is important to keep the stakeholders in the loop.
- Serve as a technical resource for applications that are developed and used by the team. These systems are used by 10¬s-100s of researchers. Training and user support is an integral part of the job.
- Compare, evaluate, and implement new features and technologies, and integrate them into the computing environment. Our team uses a diversity of programming languages (Python, R, Java, Ruby-¬on--Rails), compute environments (HPC, Cloud IaaS, Cloud PaaS), and technologies (Linux, Hadoop).
- Follow team software development methodology. This includes best practices in software design and coding, use of Github/BitBucket, Dockerhub, issue trackers, ReadTheDocs, wikis, etc.
- Mentor lower-level software developers. This may include other members in the core team, researchers who may wish to learn, interns, etc.
- Put together documents to summarize results and/or to present at conferences. For some projects, you may be expected to write peer-reviewed publications or even grant applications (NIH/NSF).
* ¬ Other duties may also be assigned
- Experience with Big Data Science research and technologies is needed.
- Experience with biomedical applications is preferred.
- Expertise in designing, developing, testing, and deploying applications.
- Proficiency with application design and data modeling.
- Ability to define and solve logical problems for highly technical applications.
- Strong communication skills with both technical and non¬technical clients.
- Ability to lead activities on structured team development projects.
- Ability to select, adapt, and effectively use a variety of programming methods.
- Knowledge of application domain.
* ¬ Consistent with its obligations under the law, the University will provide reasonable accommodation to any employee with a disability who requires accommodation to perform the essential functions of his or her job.
EDUCATION & EXPERIENCE:
- PhD in Bioinformatics, Computational Biology, Physics, Computer Science, or a related field, or a combination of education and relevant experience.
- “Stanford is an equal employment opportunity and affirmative action employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, or any other characteristic protected by law. Stanford welcomes applications from all who would bring additional dimensions to the University’s research, teaching, and clinical missions.”
Job Code: 6438
Employee Status: Fixed-Term