1

Research Assistant Deep Learning Jobs in Missouri

$80K - $110K/yr

Strong expertise in modern deep learning techniques for language processing and generation ... Collaborative culture with experienced engineers and researchers. * International environment with ...

You will work handsโ€‘on with advanced deep learning models, driving delivery of impactful ... Conduct inโ€‘depth research to explore new data sources and develop novel algorithms that advance ...

Senior Algorithm Engineer

California, MO ยท On-site

$186 - $317/hr

The innovative ideas and devices that are advancing humanity all begin with inspiration, research ... Develop machine learning, deep learning, and physics-informed models to improve measurement ...

We integrate zebrafish genetics, in vivo live imaging, and machine learning-based image analysis ... Communication, Laboratory Research, Organizing, Recordkeeping, Working Independently Grade 00 ...

$21.78 - $30.53/hr

As a community, the University of Rochester is defined by a deep commitment to Meliora - Ever ... Grant support - assist in preparation of grant materials. * Presentation preparation ...

... research or equivalent self study and experience * Have strong programming skills in Python and ... Knowledge of deep learning frameworks and methodologies * Experience in applying machine learning ...

... research or equivalent self study and experience * Have strong programming skills in Python and ... Knowledge of deep learning frameworks and methodologies * Experience in applying machine learning ...

Showing results 41-60

Research Assistant Deep Learning information

What is a research assistant deep learning?

Research Assistant Deep Learning jobs involve supporting research projects focused on artificial intelligence, specifically within the field of deep learning. These roles typically require assisting with data collection, preprocessing, running machine learning experiments, and analyzing results. Research assistants may also help with literature reviews, code development, and documentation. The position is often found in academic, industry, or research lab settings, and usually requires a solid foundation in programming, mathematics, and neural network concepts.

What does a research assistant deep learning do?

As a Research Assistant in Deep Learning, you can expect to work closely with research scientists and engineers to design, implement, and evaluate novel deep learning models. Typical daily tasks include data preprocessing, running experiments, analyzing results, and contributing to academic papers or presentations. You may also assist in developing codebases, conducting literature reviews, and collaborating with team members to solve technical challenges. The work environment is often collaborative and fast-paced, with opportunities to learn from experts and contribute to cutting-edge research projects.

What are the key skills and qualifications needed to thrive as a research assistant deep learning?

To thrive as a Research Assistant in Deep Learning, you need a strong background in machine learning, programming (especially Python), and a relevant degree in computer science or a related field. Familiarity with deep learning frameworks such as TensorFlow or PyTorch, as well as experience with data preprocessing and GPU computing, are typically required. Strong analytical thinking, attention to detail, and effective communication skills help you excel in collaborative research environments. These skills and qualities are essential for efficiently developing, testing, and improving advanced machine learning models in a fast-evolving field.

What is the difference between Research Assistant Deep Learning vs Research Assistant Machine Learning?

AspectResearch Assistant Deep LearningResearch Assistant Machine Learning
Required CredentialsBachelor's or Master's in Computer Science, Data Science, or related fields; knowledge of neural networksBachelor's or Master's in Computer Science, Data Science, or related fields; foundational ML knowledge
Work EnvironmentResearch labs, universities, tech companies focusing on AI and neural networksResearch labs, universities, tech companies working on various ML algorithms
Employer & Industry UsageAI research, deep learning projects, neural network developmentGeneral machine learning applications, data analysis, predictive modeling

Research Assistant Deep Learning specializes in neural networks and AI-focused projects, while Research Assistant Machine Learning covers a broader range of algorithms and data analysis tasks. Both roles require similar educational backgrounds but differ in technical focus and application areas.

What are popular job titles related to Research Assistant Deep Learning jobs in Missouri?

For Research Assistant Deep Learning jobs in Missouri, the most frequently searched job titles are:

What cities in Missouri are hiring for Research Assistant Deep Learning jobs?

Cities in Missouri with the most Research Assistant Deep Learning job openings:

Postdoctoral Research Associate - Oncology

Washington University

Saint Louis, MO โ€ข On-site

Full-time

Re-posted 11 days ago


Job description

Location
ST. LOUIS, MO 63110Position Summary
This posting is for a Postdoctoral Research Associate position in Dr. David Spencer's Lab in the Division of Oncology, Department of Medicine.
Dr. David Spencer is seeking a postdoctoral researcher to lead exciting new projects in the field of Cancer Genetics. The Spencer lab studies human genomics, cancer genetics, gene regulation, and the genomics and epigenetics of acute myeloid leukemia and has published articles in Cancer Cell, Cell, Leukemia, and the New England Journal of Medicine. The lab has extensive expertise in both bench science and bioinformatics and is a key member of the cancer genetics group at WashU and Siteman Cancer Center. Dr. Spencer has received funding from ASH, the Cancer Research Foundation, Doris Duke, Siteman Cancer Research Fund, and the NCI, and has extensive collaborations with the McDonnell Genome Institute.
Position will play a lead role in new studies of epigenetics, DNA methylation, and gene regulation in acute myeloid leukemia using primary human samples, cell lines, and mouse models. Responsibilities will be to design, perform, and analyze data from genomic assays including long read sequencing using the Oxford Nanopore and Pacific Biosciences platforms, single-cell multi-omics, 3D genome architecture studies (e.g., Micro-C and HiC), CUT&RUN and CUT&Tag. Experimental systems will include CRISPR/Cas9-mediated genetic and epigenetic manipulation of AML cells and massively parallel reporter assays to investigate gene regulation in leukemia. Computational analysis of these data will involve applying existing tools and developing new ones, including machine and deep learning methods. There will be opportunities for development of new cell line and animal models and testing, evaluation, and analysis of new genomic technologies. Authorship on high-profile publications resulting from this work is expected.
The postdoc will work directly with Dr. Spencer on a day-to-day basis, allowing for close mentorship to promote career development, including an independent research program and external funding. Further career and professional development training provided through the Career Center, Teaching Center, Office of Postdoctoral Affairs, and campus groups.
Job Description
Primary Duties & Responsibilities:
Information on being a postdoc at WashU in St. Louis can be found at https://postdoc.wustl.edu/prospective-postdocs-2/.
Trains under the supervision of a faculty mentor including (but not limited to):
  • Assists with grant preparation and reporting.
  • Prepares and submits papers on research.
  • Assists in the design of research experiments.
  • Evaluates research findings and assists in the reporting of the results.
  • Conscientious discharge of their research responsibilities.
  • Maintains conformity with ethical standards in research.
  • Maintains compliance with good laboratory practice including the maintenance of adequate research records.
  • Engages in open and timely discussion with their mentor regarding possession or distribution of material, reagents, or records belonging to their laboratory and any proposed disclosure of findings or techniques privately or in publications.
  • Collegial conduct towards co-trainees, staff members and members of the research group.
  • Adherence to all applicable University policies, procedures and regulations. All data, research records and materials and other intellectual property generated in University laboratories remain the property of the University.

Working Conditions:
This position works in a laboratory environment with potential exposure to biological and chemical hazards. The individual must be physically able to wear protective equipment and to provide standard care to research animals.
Salary Range:
Base pay is commensurate with experience.
The above statements are intended to describe the general nature and level of work performed by people assigned to this classification. They are not intended to be construed as an exhaustive list of all job duties performed by the personnel so classified. Management reserves the right to revise or amend duties at any time.
Required Qualifications
Education:
Ph.D., M.D. Or Equivalent Terminal Or Doctoral Degree.
Certifications/Professional Licenses:
No specific certification/professional license is required for this position.
Work Experience:
No specific work experience is required for this position.
Skills:
Not Applicable
Driver's License:
A driver's license is not required for this position.
More About This Job
At WashU, postdoctoral appointments:
  • Have a 5-year term limit that includes previous experience.

Preferred Qualifications
Education:
No additional education unless stated elsewhere in the job posting.
Certifications/Professional Licenses:
No additional certification/professional licenses unless stated elsewhere in the job posting.
Work Experience:
No additional work experience unless stated elsewhere in the job posting.
Skills:
Cell Cloning, Cell Culture Work, Cellular Biology Techniques, ChIP-Seq, Collaboration, CRISPR-Cas System, Data Analysis, Data Interpretations, Data Management, Experimentation, Laboratory Operations, Laboratory Techniques, Molecular Biology Techniques, PCR Methods, Researching, Results Reporting, RNA-Seq, Scientific Writing, Statistical Analysis, Unix Commands
Questions
For frequently asked questions about the application process, please refer to our External Applicant FAQ.
Accommodation
If you are unable to use our online application system and would like an accommodation, please email CandidateQuestions@wustl.edu or call the dedicated accommodation inquiry number at 314-935-1149 and leave a voicemail with the nature of your request.
All qualified individuals must be able to perform the essential functions of the position satisfactorily and, if requested, reasonable accommodations will be made to enable employees with disabilities to perform the essential functions of their job, absent undue hardship.
Pre-Employment Screening
All external candidates receiving an offer for employment will be required to submit to pre-employment screening for this position. The screenings will include criminal background check and, as applicable for the position, other background checks, drug screen, an employment and education or licensure/certification verification, physical examination, certain vaccinations and/or governmental registry checks. All offers are contingent upon successful completion of required screening.
Benefits Statement
Washington University in St. Louis is committed to providing a comprehensive and competitive benefits package to our employees. Benefits eligibility is subject to employment status, full-time equivalent (FTE) workload, and weekly standard hours. Please visit our website at https://hr.wustl.edu/benefits/ to view a summary of benefits.
EEO Statement
Washington University in St. Louis is committed to the principles and practices of equal employment opportunity. It is the University's policy to provide equal opportunity and access to persons in all job titles without regard to race, ethnicity, color, national origin, citizenship (where prohibited by federal law), age, religion, sex, sexual orientation, gender identity or expression, disability, protected veteran status, or genetic information.