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Multimodal Learning Jobs in Iowa (NOW HIRING)

Accenture

Forward Deployed Engineer

Des Moines, IA · On-site

Experience training, fine-tuning, and evaluating LLMs and multimodal foundation models using advanced techniques such as self-supervised and transfer learning. * Experience designing value ...

Forward Air

Forklift Operator

Carter Lake, IA · On-site

$19.82/hr

... multimodal transportation terminal, intermodal yard, warehouse, or dock environment, directly ... Perform tasks under appropriate supervision while learning equipment operation, safety protocols ...

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Multimodal Learning information

What is multimodal learning?

Multimodal learning is an area of machine learning that involves integrating and processing information from multiple types of data, such as text, images, audio, and video. The goal is to create models that can understand and make predictions based on more than one data modality, similar to how humans use various senses. This approach is used in applications like speech recognition with visual cues, image captioning, and video analysis. By combining different data types, multimodal learning systems can achieve better accuracy and more robust understanding.

What is the difference between Multimodal Learning vs Data Scientist?

AspectMultimodal LearningData Scientist
Required CredentialsAdvanced degrees in AI, Machine Learning, or Computer ScienceBachelor's or Master's in Data Science, Statistics, or related fields
Work EnvironmentResearch labs, AI development teams, academiaBusiness, tech companies, analytics teams
Industry UsageAI research, multimedia applications, roboticsData analysis, predictive modeling, business insights

Multimodal Learning focuses on developing AI models that process and integrate multiple data types like images, text, and audio. Data Scientists analyze data to extract insights, build models, and support decision-making. While both roles involve data and algorithms, Multimodal Learning is specialized in AI model development for complex data integration, whereas Data Scientists work broadly across data analysis and interpretation.

What are the key skills and qualifications needed to thrive as a Multimodal Learning Specialist, and why are they important?

To excel as a Multimodal Learning Specialist, you need a solid background in machine learning, data science, and computer vision, often supported by an advanced degree in a related field. Familiarity with deep learning frameworks like TensorFlow or PyTorch, experience integrating data from diverse sources (e.g., text, audio, images), and knowledge of relevant algorithms are crucial. Strong problem-solving abilities, creativity, and effective collaboration are standout soft skills for this role. These competencies are vital for developing innovative models that can process and interpret complex, multi-source data to drive impactful AI solutions.

What are some common challenges faced by professionals working in multimodal learning roles, and how can they be addressed?

Professionals in multimodal learning frequently encounter challenges related to integrating and aligning data from multiple sources, such as text, images, audio, or video. Ensuring data quality and consistency across modalities can be complex, and developing models that effectively combine heterogeneous information often requires advanced technical skills and innovative thinking. Collaboration with domain experts and other data scientists is key to overcoming these obstacles, as is staying up to date with the latest research and tools in machine learning. Regular team meetings and cross-disciplinary workshops can help foster a collaborative environment and promote knowledge sharing.
What are popular job titles related to Multimodal Learning jobs in Iowa? For Multimodal Learning jobs in Iowa, the most frequently searched job titles are:
What job categories do people searching Multimodal Learning jobs in Iowa look for? The top searched job categories for Multimodal Learning jobs in Iowa are:
What cities in Iowa are hiring for Multimodal Learning jobs? Cities in Iowa with the most Multimodal Learning job openings:
Multimodal Learning jobs near you
50% Research Associate - Infectious Diseases

50% Research Associate - Infectious Diseases

The University Of Iowa

Iowa City, IA • On-site

Other

Posted 12 days ago

University Of Iowa rating

6.8

Company rating: 6.8 out of 10

Based on 84 frontline employees who took The Breakroom Quiz

412th of 541 rated colleges and universities

Job description

BASIC FUNCTION

The Research Assistant - Computational Scientist supports research efforts in Dr. Priya Issuree' laboratory, which studies epigenetic mechanisms of gene regulation in immune cells. This position will provide computational support by analyzing experiments across laboratory projects and will require analysis, organization and interpretation of both newly generated and existing genomic datasets and using computational tools to perform integrated and multimodal data analyses, under the PI's supervision. This role involves the development, implementation, and maintenance of computational pipelines; application of statistical tests and rigor to generation of integrative models of gene function in immune cells. The RA will work closely with scientists, trainees, and collaborators and will contribute to study design, data interpretation, visualization, and dissemination. The position may also support data infrastructure efforts, including computational tools that enhance data sharing, reproducibility, and discovery.

KEY AREAS OF RESPONSIBILITY

Computational and Bioinformatic Analysis:

  • Perform bioinformatic analyses (scRNA-Seq, ATAC-Seq, Cut and Tag, DNA methylation) based upon protocols developed by the principal investigator of the research project.

  • Perform combinatorial/multimodal bioinformatic analyses and appropriate statistical analyses, and generate graphical outputs to visualize findings.

  • Use multimodal datasets to develop new hypotheses and generate avenues for biological validation and testing by other team and lab members, with assistance from the PI

  • Generate figures, summaries, and visualizations for manuscripts, presentations, grant applications, and internal reports.

Data management, analysis and compliance:

  • Proper documentation of bioinformatic codes used for different projects and establish a systematic approach to easily locate, analyze, and store data.

  • Develop and rigorously test new pipelines as necessary and ensure methods used are scientifically sound

  • Assist in preparing documentation of computational methods for publications and regulatory or funding requirements, as directed by the Principal Investigator

  • Develop independence in troubleshooting, analysis, and propose modifications to protocols; present results at team meetings and meet with collaborators as needed.

  • Adhere to safety and compliance guidelines in the laboratory.

  • Adhere to Quality Assurance protocols to maintain the validity and integrity of research data.

Administrative and Project Management:

  • Assist with manuscript and grant preparations, under PI's supervision

  • Track various indicators of project progress and summarize in reports to the research team. Prepare data/ project updates and results for discussion at weekly meeting with PI.

Facilities and Equipment Management:

  • Assist in the maintenance of cloud servers and external servers used for data storage at the university

  • Ensuring proper functioning of all hardware and software needed for data analysis and storage

REQUIRED QUALIFICATIONS

  • Bachelor's degree in computational biology, Bioinformatics, Data Science, Biostatistics, Computer Science, Biomedical Engineering, or a closely related quantitative or lifescience field, or equivalent combination of education and progressively responsible experience in a research laboratory environment is required

  • Experience performing computational analysis of highthroughput biological data, such as singlecell RNA sequencing (scRNAseq) and ATAC Seq

  • Proficiency in at least one programming language commonly used in computational biology (e.g., R and/or Python).

  • Working knowledge of standard bioinformatic workflows, including data quality control, normalization, statistical analysis, and data visualization.

  • Ability to follow established computational pipelines and analytical protocols under general supervision.

  • Strong attention to detail and ability to document computational methods, code, and results.

  • Effective written and verbal communication skills, including the ability to explain computational results to collaborators with varied scientific backgrounds.

  • Ability to work collaboratively as part of a multidisciplinary research team and manage multiple projects simultaneously.

DESIRED QUALIFICATIONS:

  • Prior experience with integration of multimodal datasets (e.g., transcriptomic + epigenomic, data).

  • Basic experience applying machine learning or predictive modeling approaches to biological data.

  • Experience developing or contributing to reproducible workflows using version control systems (e.g., Git).

  • Experience generating publicationquality figures and contributing to manuscripts, abstracts, or grant applications.

  • Master's degree in computational biology, Bioinformatics, Data Science, Biostatistics, Computer Science, Biomedical Engineering, or a closely related quantitative or lifescience field.

Position and Application Details:

In order to be considered for an interview, applicants must upload the following documents and mark them as a "Relevant File" to the submission:

  • Resume
  • Cover Letter

Job openings are posted for a minimum of 7 calendar days and may be removed from posting and filled any time after the original posting period has ended.

Successful candidates will be required to self-disclose any conviction history and will be subject to a criminal background check and credential/education verification. Up to 5 professional references will be requested at a later step in the recruitment process.

For additional questions, please contact ashley-rayer@uiowa.edu.

Additional Information
  • Classification Title: Research Associate
  • Appointment Type: Professional and Scientific
  • Schedule: Part-time
Compensation
  • Pay Level: 4A
Contact Information
  • Organization: Healthcare
  • Contact Name: Ashley Nelson
  • Contact Email: ashley-rayer@uiowa.edu

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