AI/ML Intern - Radiation Oncology

We need to output HTML fragment with sections: About the role? The posting includes a paragraph about Mayo Clinic being top-ranked etc. That's like an "About the role" or maybe "About Mayo Clinic". The instructions: use

for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule). Use

• for any list of duties/requirements/benefits, and

  for prose. Do NOT repeat the job title as a heading (the page already shows it) and do NOT put Job ID / requisition numbers as headings — fold minor metadata into a short

  or drop it. Preserve ALL substantive information; do NOT invent or summarize away detail. Remove cookie/navigation/legal/EEO/equal-opportunity/scam-warning boilerplate, duplicated lines, and application instructions. IMPORTANT: include a section ONLY when the posting has real, specific content for it — never emit a heading followed by filler/placeholder text (e.g. "commensurate with experience", "not specified", "N/A", "varies", "TBD") and never create Pay/Schedule/Benefits sections unless the posting actually states them. Prefer a few substantive sections over many thin ones. Output ONLY the HTML fragment — no /, no markdown code fences. We need to decide which sections to include based on content. Content includes: - Intro paragraph: "Why Mayo Clinic Mayo Clinic is top-ranked...". That's about the organization, maybe "About the role" or "About Mayo Clinic". We'll treat as "About the role" (or "About Mayo Clinic"). - Responsibilities: a paragraph describing intern responsibilities, plus bullet list of problem areas: diagnostic analytics such as image analysis, signal processing and pattern recognition, NLP, scheduling, risk analysis and prevention, outcome analysis, targeting and socio-economic behaviors, personalization – including sentiment, interests and affinities modeling, and process improvement (e.g. making sure patients are referred to the care teams they need). That's a list. - Also responsibilities: "Interns will interact with vast amounts of clinical and non-clinical data (external data sources, digital, etc.). Interns will learn the data science lifecycle including data acquisition, transformation, data engineering, exploratory data analysis, feature engineering, algorithm development, and algorithm deployment into a relevant clinical and/or business context. Interns are expected to help formulate analytical questions, perform hypothesis testing, algorithm optimization, algorithm deployment, and integrate feedback rapidly from stakeholders. Candidate needs to have an open mind and ability to take concepts developed by other industries and apply them to healthcare. Candidates should be effective communicators and good team players. Candidates who have coursework, projects, and evidence of interest in data science (e.g. participating in Kaggle competitions) but lack industry experience are ideal for this position." That's more responsibilities and also qualifications? Might be part of responsibilities. - Qualifications: "Must reside within the continental US. This vacancy is not eligible for sponsorship/we will not sponsor or transfer visas for this position. Also, Mayo Clinic DOES NOT participate in the F-1 STEM OPT extension program. Current enrollment or recent graduate of undergrad or grad program in: Computer Science, Information Technology, Data Science, Physics, Statistics/Biostatistics, or other related field with strong quantitative analytical skills. School or project experience in applying data science approaches/tools. Proven written and oral communication skills are essential.AI experience/exposure or familiarity with AI principles is required. Courses and comfort level with at least one of the following: computer programming, machine learning, graph theory, algorithms, statistics, SQL and linear algebra are essential for success. Experience with major programming languages is beneficial. Demonstrated initiative/innovation in coursework and projects. Experience with data science development tools building algorithms on structured data is preferred. Experience working with unstructured data such as natural language, images, genetics, or signal processing (e.g. EKG) is preferred. Experience with C/C++/Java or other systems programming languages and software engineering methodology is not required but beneficial. Candidates with exceptional web-stack data visualization (Angular/D3) experience will also be considered." - Exemption Status: Nonexempt - Compensation Detail: $25.00 / hour - Benefits Eligible: No - Schedule: Part Time Hours/Pay Period Supplemental/PRN Schedule Details Monday through Friday, 8-5 This is a hybrid position and must be located within 100 miles of a Mayo Clinic campus. Weekend Schedule None International Assignment No - Site Description: paragraph about locations. - Equal Opportunity boilerplate: remove. - Recruiter: Kianne Hinkle (metadata, maybe include as short p). We need to include sections only when there is real specific content. So we can have sections: About the role (intro paragraph), Responsibilities (list of duties), Qualifications (list), Pay (compensation), Schedule (details), Benefits (maybe we have Benefits Eligible: No - that's specific content, so we can include Benefits section stating "Not eligible for benefits". However instruction: never create Pay/Schedule/Benefits sections unless the posting actually states them. It does state Benefits Eligible No, so we can include Benefits section with that info. Pay: $25.00/hour. Schedule: Part Time, Supplemental/PRN, Monday-Friday 8-5, hybrid, within 100 miles, weekend none. We could combine Pay and Schedule into separate sections or maybe combine? The instruction: prefer a few substantive sections over many thin ones. But we need to include sections only when there is real specific content. Could we combine Pay and Schedule into one "Compensation and Schedule" section? But they gave examples of headings: Pay, Schedule, Benefits separate. It's okay to have multiple sections if they have content. However "prefer a few substantive sections over many thin ones" suggests we shouldn't create many sections with little content. But each of these has substantive content. We could have sections: About the role, Responsibilities, Qualifications, Pay, Schedule, Benefits, Site Description (maybe as "About Mayo Clinic" or "Location"). Site Description is substantive; we could include as "Location" or "Site Description". Not in the example headings list but we can still use

  for any heading? The instruction: use

  for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule). It says e.g., not exclusive. So we can use other headings like "Location" or "Site Description". Probably okay. We need to avoid boilerplate: Equal Opportunity, Recruiter maybe minor metadata; we could fold recruiter into a short p under maybe "Contact" but not required. Could drop it. We need to preserve all substantive information; do not invent or summarize away detail. So we need to keep all details from the posting. Let's extract substantive content: Intro paragraph: "Why Mayo Clinic Mayo Clinic is top-ranked in more specialties than any other care provider according to U.S. News & World Report. As we work together to put the needs of the patient first, we are also dedicated to our employees, investing in competitive compensation and comprehensive benefit plans – to take care of you and your family, now and in the future. And with continuing education and advancement opportunities at every turn, you can build a long, successful career with Mayo Clinic." That's about Mayo Clinic. Responsibilities: The paragraph: "Interns will utilize statistics and computer science to solve complex problems in healthcare. Problem areas include: diagnostic analytics such as image analysis, signal processing and pattern recognition, NLP, scheduling, risk analysis and prevention, outcome analysis, targeting and socio-economic behaviors, personalization – including sentiment, interests and affinities modeling, and process improvement (e.g. making sure patients are referred to the care teams they need). The Intern will interact with vast amounts of clinical and non-clinical data (external data sources, digital, etc.). Interns will learn the data science lifecycle including data acquisition, transformation, data engineering, exploratory data analysis, feature engineering, algorithm development, and algorithm deployment into a relevant clinical and/or business context. Interns are expected to help formulate analytical questions, perform hypothesis testing, algorithm optimization, algorithm deployment, and integrate feedback rapidly from stakeholders. Candidate needs to have an open mind and ability to take concepts developed by other industries and apply them to healthcare. Candidates should be effective communicators and good team players. Candidates who have coursework, projects, and evidence of interest in data science (e.g. participating in Kaggle competitions) but lack industry experience are ideal for this position." We could split into a list for problem areas and rest as prose. Qualifications: All the bullet-like statements. We need to format as

  • for any list of duties/requirements/benefits. So for problem areas list, we can make a
    . For qualifications, we can also make a
    (list of requirements). For benefits, we have just "Benefits Eligible No" - could be a

    or

    • but it's not a list; we can just

      Benefits: Not eligible.

      . Pay:

      Pay: $25.00 per hour.

      Schedule: details: Part Time, Supplemental/PRN, Monday-Friday 8-5, hybrid, must be located within 100 miles of a Mayo Clinic campus, weekend none. Could be a

      or

      . We'll do

      . Site Description: paragraph about locations. We also have Exemption Status Nonexempt - could be included under Pay or as its own section? Not in examples but we could include under Pay section or as a separate "Exemption". Might be minor; we could fold into Pay section as a note. Recruiter: Kianne Hinkle - could be minor metadata; we could drop or include as

      Recruiter: Kianne Hinkle

      . Probably okay to drop as minor. We must not include EEO boilerplate. Now construct HTML:

      About the role

      Why Mayo Clinic Mayo Clinic is top-ranked in more specialties than any other care provider according to U.S. News & World Report. As we work together to put the needs of the patient first, we are also dedicated to our employees, investing in competitive compensation and comprehensive benefit plans – to take care of you and your family, now and in the future. And with continuing education and advancement opportunities at every turn, you can build a long, successful career with Mayo Clinic.

      Responsibilities

      Interns will utilize statistics and computer science to solve complex problems in healthcare. Problem areas include:

      • diagnostic analytics such as image analysis, signal processing and pattern recognition
      • NLP
      • scheduling
      • risk analysis and prevention
      • outcome analysis
      • targeting and socio-economic behaviors
      • personalization – including sentiment, interests and affinities modeling
      • process improvement (e.g. making sure patients are referred to the care teams they need)

      The Intern will interact with vast amounts of clinical and non-clinical data (external data sources, digital, etc.). Interns will learn the data science lifecycle including data acquisition, transformation, data engineering, exploratory data analysis, feature engineering, algorithm development, and algorithm deployment into a relevant clinical and/or business context. Interns are expected to help formulate analytical questions, perform hypothesis testing, algorithm optimization, algorithm deployment, and integrate feedback rapidly from stakeholders. Candidate needs to have an open mind and ability to take concepts developed by other industries and apply them to healthcare. Candidates should be effective communicators and good team players. Candidates who have coursework, projects, and evidence of interest in data science (e.g. participating in Kaggle competitions) but lack industry experience are ideal for this position.

      Qualifications

      • Must reside within the continental US.
      • This vacancy is not eligible for sponsorship; we will not sponsor or transfer visas for this position.
      • Mayo Clinic does not participate in the F-1 ST