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Trainee Google Biomedical Engineering Jobs in Texas

D. in Bioinformatics, Computational Biology, Genetics, Computer Science, Biomedical Engineering, or ... or Google Cloud). • Experience with large-scale genomic databases and real-world clinical data ...

... Google Sheets) * Drive process improvements to enhance systemic compliance and quality standards ... Background in Biomedical or Electrical Engineering * 1-3 years of experience in Quality Systems

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Trainee Google Biomedical Engineering information

What is the difference between Trainee Google Biomedical Engineering vs Biomedical Technician?

AspectTrainee Google Biomedical EngineeringBiomedical Technician
Required CredentialsTypically pursuing or holding a degree in biomedical engineering or related fieldAssociate's or bachelor's degree in biomedical technology or related field
Work EnvironmentResearch labs, tech companies, or corporate settings, often involving product developmentHospitals, clinics, or repair facilities focusing on equipment maintenance
Employer & Industry UsageTech giants like Google, healthcare startups, biomedical firmsHospitals, medical device companies, service providers

While both roles involve biomedical technology, Trainee Google Biomedical Engineering focuses on innovative product development and research within tech companies, often requiring ongoing education. Biomedical Technicians primarily maintain and repair medical equipment in clinical settings. The roles differ in environment, responsibilities, and career pathways, but both contribute to advancing healthcare technology.

Does Google hire biomedical engineers?

Google hires biomedical engineers for roles related to healthcare technology, medical data analysis, and health-related research projects. These positions often require knowledge of biomedical systems, programming skills, and familiarity with medical devices or data standards. Opportunities may be available in research labs, health-focused divisions, or through collaborations with healthcare organizations.

What are the most commonly searched types of Google Biomedical Engineering jobs in Texas?

The most popular types of Google Biomedical Engineering jobs in Texas are:

What are popular job titles related to Trainee Google Biomedical Engineering jobs in Texas?

For Trainee Google Biomedical Engineering jobs in Texas, the most frequently searched job titles are:

What cities in Texas are hiring for Trainee Google Biomedical Engineering jobs?

Cities in Texas with the most Trainee Google Biomedical Engineering job openings:

Computational Research Scientist, Simmons Cancer Center

4492

Dallas, TX • On-site

Full-time

Medical, Retirement, PTO

This job post has expired today. Applications are no longer accepted.


Job description

WHY UT SOUTHWESTERN?
With over 75 years of excellence in Dallas-Fort Worth, Texas, UT Southwestern is committed to excellence, innovation, teamwork, and compassion. As a world-renowned medical and research center, we strive to provide the best possible care, resources, and benefits for our valued employees. Ranked as the number 1 hospital in Dallas-Fort Worth according to U.S. News & World Report, we invest in you with opportunities for career growth and development to align with your future goals. Our highly competitive benefits package offers healthcare, PTO and paid holidays, on-site childcare, wage, merit increases and so much more. We invite you to be a part of the UT Southwestern team where you'll discover a culture of teamwork, professionalism, and a rewarding career!
JOB SUMMARY
Leads the design and implementation of High-Performance Scientific Computing infrastructure. Performs and supports scientific research using technical knowledge of software, software development, complex databases, high-performance computing, and/or hardware in a complex computing environment. Performs scientific research using knowledge of formalisms and algorithms from mathematics, statistics, and/or computer science.

The Center for Cellular Therapies and Cancer Immunology in the Harold C. Simmons Comprehensive Cancer Center is looking to hire a Computational Research Scientist at the interface of machine learning, cancer genomics, and immunology. You will build and apply computational methods that turn large-scale multi-omic and functional datasets into validated therapeutic hypotheses, while working side by side with experimental and translational scientists to bring those hypotheses to the clinic.

This is a senior, high-autonomy position suited to someone who wants their models to drive biological discovery to therapies. You will help set scientific direction, mentor junior computational and experimental scientists, and serve as the analytical backbone of a program developing novel immunotherapies within a new center.


What you will do
Build predictive models that integrate genomic, transcriptomic, epigenomic, single-cell, and functional-screen data to nominate novel therapeutic targets in cancer and the tumor immune microenvironment.
Drive immunotherapy engineering by applying machine learning to antigen and neoantigen discovery, de novo protein design, and the optimization of engineered immune cells.
Develop methods for interpreting high-dimensional and perturbation data, including deep learning approaches to sequence, structure, and single-cell readouts.
Partner closely with wet-lab scientists to design experiments, prioritize candidates for validation, and iterate rapidly between computation and the bench.
Lead and mentor trainees and staff, set analytical standards, and help shape the scientific roadmap of the program.
Communicate results through high-impact publications, presentations, and collaborations across UT Southwestern's research and clinical community.

Areas of focus
Depending on your interests and strengths, your work can center on identifying novel cancer immunotherapy targets and/or developing novel therapeutics. Approaches may include:
Machine learning applied to multi-omic, single-cell, and functional data
Clinical-molecular correlations that link genotype and tumor biology to therapeutic response
De novo protein design
Computational proteomics

Preferred Qualifications
Education
oPh.D. in Bioinformatics, Computational Biology, Biomedical Engineering, or related field
oMaster's degree in computer science, Electrical Engineering, or related field
Experience
o2 years experience in driving computational biology/machine learning projects.
o4 years experience in driving computational biology/machine learning projects with Master's Degree.
oPost-doctoral fellowship preferred.

BENEFITS
UT Southwestern is proud to offer a competitive and comprehensive benefits package to eligible employees. Our benefits are designed to support your overall wellbeing, and include:

  • PPO medical plan, available day one at no cost for full-time employee-only coverage
  • 100% coverage for preventive healthcare-no copay
  • Paid Time Off, available day one
  • Retirement Programs through the Teacher Retirement System of Texas (TRS)
  • Paid Parental Leave Benefit
  • Wellness programs
  • Tuition Reimbursement
  • Public Service Loan Forgiveness (PSLF) Qualified Employer
  • Learn more about these and other UTSW employee benefits!


EXPERIENCE AND EDUCATION
Required

  • Education
    PhD In Computer Science, Electrical Engineering, or related field or
    Master's Degree In Computer Science, Electrical Engineering, or related field
  • Experience
    2 years Experience in software development/engineering and/or HPC systems management with PhD. or
    4 years Experience in software development/engineering and/or HPC systems management with Master's Degree.


JOB DUTIES

  • Designs and implements the high-performance scientific computing infrastructure for for large, multi-institution projects, including software applications, workflows, servers, databases, long-term and short-term storage solutions, and cloud services.
  • Serves as a domain expert for research and industry collaborations on biomedical computational methods, algorithms and platforms. Subject matter expert in multiple areas of computing technology.
  • Leads and develops proof-of-concepts (PoCs) for solutions applied to biomedical and clinical science use-cases by working closely with industry collaborators.
  • Designs, develops, implements and optimizes algorithms and scientific workflows for high dimensional data in biomedical and clinical sciences.
  • Develops software and methods to explore, analyze and visualize biological data sets.
  • Demonstrates and craft applications of cutting-edge visual computing technologies and connect them to core infrastructure.
  • Report research results in journal articles, conference papers, and technical manuals.
  • Mentor and train staff, postdoctoral fellows, and graduate students.
  • Supports faculty and students in adapting computational strategies to leverage high-performance computing, working with a range of systems and technologies such as compute cluster, parallel file systems, high speed interconnects, GPU-based computing and data servers.
  • Performs other duties as needed

SECURITY AND EEO STATEMENT
Security
This position is security-sensitive and subject to Texas Education Code 51.215, which authorizes UT Southwestern to obtain criminal history record information. To the extent this position requires the holder to research, work on, or have access to critical infrastructure as defined in Section 117.001(2) of the Texas Business and Commerce Code, the ability to maintain the security or integrity of the critical infrastructure is a minimum qualification to be hired and to continue to be employed in the position.
EEO
UT Southwestern Medical Center is committed to an educational and working environment that provides equal opportunity to all members of the University community. As an equal opportunity employer, UT Southwestern prohibits unlawful discrimination, including discrimination on the basis of race, color, religion, national origin, sex, sexual orientation, gender identity, gender expression, age, disability, genetic information, citizenship status, or veteran status.