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Machine Learning Biomedical Internship Jobs in Missouri

... internship * At least 6 months experience or academic work using open source programming languages for data analysis * At least 6 months of experience or academic work using machine learning ...

Production OSU Intern

Jamesport, MO ยท On-site

$17.50/hr

... to learning, collaboration, and innovation, Smithfield offers challenging and rewarding careers ... Our internships are typically 10 weeks. Hourly Competitive Starting Pay - $17.50/hour Core ...

... to learning, collaboration, and innovation, Smithfield offers challenging and rewarding careers ... Our internships are typically 10 weeks. Hourly Competitive Starting Pay - $17.50/hourCore ...

AI Engineer

Troy, MO ยท On-site

$120 - $180/hr

Build, train, and evaluate machine learning models for classification, prediction, and simulation ... Internship, academic, or project experience building and deploying models or AI features end-to-end

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Machine Learning Biomedical Internship information

What is a machine learning biomedical internship?

A Machine Learning Biomedical Internship is a temporary position where students or recent graduates work with professionals to apply machine learning techniques in the biomedical field. Interns typically assist with data analysis, model development, and research projects that involve biological or medical data. The goal is to gain practical experience in using artificial intelligence to solve healthcare challenges, such as disease prediction, medical imaging, or drug discovery. These internships often require knowledge of programming languages like Python and familiarity with machine learning frameworks. They provide valuable hands-on experience and networking opportunities for those interested in biomedical data science careers.

What types of projects do interns typically work on during a machine learning biomedical internship?

Interns in Machine Learning Biomedical roles often contribute to projects involving the development and validation of algorithms for analyzing medical data, such as imaging, genomics, or electronic health records. They may assist with data preprocessing, model training, and performance evaluation under the guidance of experienced researchers or engineers. Collaboration is common, as interns often work closely with interdisciplinary teams including data scientists, clinicians, and software engineers. This hands-on experience provides valuable exposure to real-world biomedical challenges while strengthening both technical and communication skills.

What are the key skills and qualifications needed to thrive as a machine learning biomedical intern, and why are they important?

To excel as a Machine Learning Biomedical Intern, you need a solid background in computer science, statistics, and biology, often supported by coursework or a degree in related fields. Familiarity with programming languages like Python or R, experience with machine learning libraries (such as TensorFlow or scikit-learn), and knowledge of data analysis tools are typically required. Strong problem-solving skills, attention to detail, and the ability to communicate complex technical concepts clearly are crucial soft skills. These competencies enable interns to develop effective models, collaborate with multidisciplinary teams, and contribute meaningful insights to biomedical research projects.

What are popular job titles related to Machine Learning Biomedical Internship jobs in Missouri?

For Machine Learning Biomedical Internship jobs in Missouri, the most frequently searched job titles are:

What job categories do people searching Machine Learning Biomedical Internship jobs in Missouri look for?

The top searched job categories for Machine Learning Biomedical Internship jobs in Missouri are:

What cities in Missouri are hiring for Machine Learning Biomedical Internship jobs?

Cities in Missouri with the most Machine Learning Biomedical Internship job openings:

Principal, Machine Learning Scientist

BigHat

California, MO โ€ข On-site

$254 - $290/hr

Other

Medical, Dental, Vision, Retirement

Posted 4 days ago


Job description

Principal, Machine Learning Scientist

Department: DS/ML (Data Science/Machine Learning)

Employment Type: Full Time

Location: San Mateo, CA

Reporting To: Hunter Elliot

Description

The role: We are seeking a creative, accomplished Principal Machine Learning Scientist to advance the state of the art in ML-driven therapeutic antibody design.

At BigHat Biosciences our full-stack antibody drug development platform uses ML to drive every stage from discovery to optimization. Our roboticized high-throughput wet-lab continually adds to our large proprietary datasets, which are piped through a custom LIMS++ data management and orchestration layer to automatically update and deploy the latest models. This makes the development of complex, next-gen therapeutics trivially parallelizable, at a pace which only accelerates as we develop better ML tooling.

You're not interested in just git-cloning the latest NeurIPS pub and swapping out the dataset. Motivated by an enthusiasm for the possibility of addressing unmet patient needs and a curiosity about the underlying biology, you'll apply your world-class ML skillset to refine and expand this state-of-the-art protein engineering platform. Success will mean not only hands-on methods development, but helping shape the direction for future ML research, and actively participating in the application of our platform to the accelerated design of new therapeutics.

Key Responsibilities
  • Design and implement the next state-of-the-art generative models of antibody sequence and structure, and predictive models of antibody properties, trained on proprietary internal datasets of thousands to millions of antibodies.
  • Provide leadership, technical guidance, and mentorship to other ML and data science FTEs and interns.
  • Help set strategy for future ML research, driven by a strong high-level understanding of BigHat programs and operations as well as real-world drug development challenges.
  • Develop, refine, and deploy de novo design methods for generating initial hits to challenging, therapeutically interesting targets.
  • Develop multi-modality, multi-objective iterative protein sequence optimization approaches to lab-in-the-loop antibody design problems for validation and deployment in our high-throughput wet lab - at BigHat success is only declared upon synthesis of real antibodies with drug-like properties.
  • Maintain an in-depth understanding of the current state-of-the-art in ML-driven protein engineering, both in the literature and at BigHat.
  • Share your findings at top-tier conferences and publish in leading scientific journals to advance the field of protein engineering.
  • Provide ML expertise and support for ongoing therapeutics programs, directly contributing to the development of new drugs.
  • Collaborate with our engineering team to ensure maximal efficiency in the automated and agentic deployment of our latest models to our therapeutics programs.
  • Work closely with an interdisciplinary team of drug developers, wet lab scientists, automation specialists, data scientists, etc. to identify inefficiencies or potential improvements in BigHat's platform, and plan and prioritize ML methods development accordingly.
Skills Knowledge and Expertise
  • PhD in ML/CS or in the hard sciences with 5+ years experience post-graduation in developing and applying novel ML methods, and a strong quantitative background.
  • Publications in major ML conferences and/or leading journals, and an extensive demonstrable track record developing and applying novel ML in industry.
  • Strong competency in Python, familiarity with PyTorch, and experience with modern software engineering best practices.
  • Excellent communication skills, sufficient biomedical domain knowledge to interact effectively with diverse scientific teams.
  • Enjoys a fast-paced environment and excels at executing across multiple projects.
  • Familiarity with the current state-of-the-art in ML-driven protein engineering
  • Nice-to-haves include experience with de novo design, NGS data, Bayesian optimization, familiarity with antibody biology and drug development, and experience training and deploying models on AWS.
Total Rewards

The salary estimated for this position is $254,000 - $290,000 + bonus + options + benefits. Compensation will vary depending on job-related knowledge, skills, and experience. Actual compensation will be confirmed in writing at the time of the offer.

What BigHat Offers:

  • Range of health insurance plan options through Anthem and Kaiser (monthly credit if benefit waived)
  • Dental, and vision coverage through Guardian
  • Additional well-being benefits through Nayya, OneMedical, Wagmo, Rula, and more
  • 401(k) with company match
  • DTO, two weeks of company-wide shutdown, and 12 company holidays
  • Paid parental leave
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