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Field
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clinical data and machine learning algorithms. The main activities include: Data Processing: • Collection of historical patient data (demographics, clinical history, outcomes of interventions). Data cleaning
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clinical data and machine learning algorithms. The main activities include: Support for AI Model Development: • Collaborating on the training of predictive models under the supervision of the scientific team
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. Implementation of signal detection algorithms and triangulation ; 4. Planning and participating in field tests to evaluate system performance; 5. Reporting and disseminating the work developed (ideally with a
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without regard to race, color, creed, religion, age, marital status, national origin, sex, sexual orientation, disability, genetic information or status as a disabled veteran or Vietnam-era veteran. Non
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or mental), Gender, Gender Identity (including Nonbinary or Transgender), Gender Expression, Genetic Information, Marital Status, Medical Condition, Nationality, Pregnancy or related conditions, Race
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and prohibits discrimination on the basis of Age, Disability (physical or mental), Gender, Gender Identity (including Nonbinary or Transgender), Gender Expression, Genetic Information, Marital Status
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. The university prohibits discrimination based on age, ancestry, caste, color, disability, ethnicity, gender, gender expression, gender identity, genetic information, marital status, medical condition, military
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orientation, marital status, family situation, economic situation, education, social origin or condition, genetic heritage, reduced working capacity, disability, chronic illness, nationality, ethnic origin
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identity, gender expression, pregnancy, pregnancy-related conditions, genetic information, or protected veteran’s status. The University does not discriminate on the basis of sex in the education program or
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, including minorities, women, and persons with disabilities. The College does not discriminate on the basis of age, color, disability, gender identity, genetic information, national origin, race, religion