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PHD BIOS DAT - Biostatistics and Data Science (PhD)

Program Overview

Program Level

ACADEMIC_LEVEL_GRADUATE

Program Code

PHD BIOS DAT

Learning Outcomes

Name

Lead cutting-edge research in statistical methodology, genetic epidemiology, or data science.

Name

Act as a consummate resource in the design, analysis, and interpretation of a wide array of studies.

Name

Use standard statistical (R, SAS, and Stata) and computer (Python) programming languages to reproducibly explore and visualize data, fit models, conduct inference, and translate analysis results.

Name

Conduct all facets of big data analysis, including the extraction, storage, manipulation, and analysis of massive datasets, using data science techniques and machine learning.

Name

Collaborate with non-statisticians with authority, communicating complex findings to the scientific and general community to improve health care and prevent disease.

Requisites

The PhD degree is a research degree and is not conferred solely as a result of formal course work, no matter how superior and extensive. The program leading to the PhD degree represents more than the sum of time in residence, and the plans of study listed below are only a minimum. To receive the doctoral degree, the candidate must demonstrate evidence of proficiency and distinctive attainment in a special field, and a recognized ability for independent investigation as presented in a dissertation based upon original research.

Comprehensive Examination

The comprehensive examination covers four first-year courses, namely BDS 721: Analytics, BDS 722: Advanced Analytics, BDS 741: Statistical Inference I, and BDS 751: Statistical Inference in Genetics. The comprehensive exam is offered in May to students who have completed the requisite coursework. Students must successfully pass this exam before undertaking the qualifying examination.

Qualifying Examination and Admission to Candidacy

The qualifying examination is given to graduate students in good academic standing upon completion of coursework successful passage of the comprehensive examination. The qualifying examination must be successfully completed for admission to candidacy for the doctor of philosophy degree. This examination includes a 45-minute oral presentation of a biostatistics or data science project that the student completed under the mentorship of a program faculty member. The examination panel includes the research mentor and two additional faculty from the Biostatistics and Data Science program.

Dissertation

The dissertation must show the originality of thought and demonstrate the results of independent investigation. It should contribute to the advancement of knowledge, exhibit mastery of the subject literature, and be written with an acceptable degree of literary skill. The dissertation, written according to the prescribed form, is prepared under the direction of the candidate's advisor and must be approved by the candidate's doctoral advisory committee and the Dean of the SOPH. This approval must be obtained and all other requirements completed by the date given in the official academic calendar. Guidelines outlining the prescribed form for a student's written thesis can be found on the SOPH Dissertation and Thesis website.

Dissertation Proposal and Dissertation Defense

The oral dissertation proposal defense to the doctoral advisory committee and dissertation defense to the public are mandatory for the successful completion of the dissertation. The candidate's advisory committee will oversee the dissertation process. See the SOPH Thesis and Dissertation Defense policy for details.

Required Coursework

Students must successfully complete BDS 706: Ethics in Biostatistics and Data Science Research and Practice.

Publication Requirement

A student enrolled in the Biostatistics and Data Science Doctor of Philosophy (PhD) program must have the results of their co-author research accepted for publication and the results of their first-author research submitted for publication before the awarding of the degree, as outlined in the SOPH Student Publication Requirement policy.

Plan of Study

Year 1 – Fall

BDS 721

Analytics

3

BDS 741

Statistical Inference I

3

BDS 754

Principles of Programming with Python

3

TOTAL TERM HOURS

9

Year 1 – Spring

BDS 706

Ethics in Biostatistics and Data Science Research and Practice

1

BDS 722

Advanced Analytics

3

BDS 723

Statistical Programming with R

3

BDS 751

Statistical Inference in Genetics

3

TOTAL TERM HOURS

10

Year 2 – Summer

BDS 797

Biostatistics & Data Science Internship

1

TOTAL TERM HOURS

1

Year 2 – Fall

BDS 725

Survival Analysis

3

BDS 761

Data Science and Machine Learning I

3

PHS 710 or MSCI 710

Epidemiology I**

3

TOTAL TERM HOURS

9

Year 2 – Spring

BDS 724

Longitudinal and Multilevel Models

3

BDS 765

Data Science and Machine Learning 2

3

BDS 792

Statistical Consulting

3

TOTAL TERM HOURS

9

Year 3 – Summer

BDS 797

Biostatistics & Data Science Internship

9

TOTAL TERM HOURS

9

Year 3 – Fall

BDS 739

Computational Statistics

3

BDS 750

Study Design and Clinical Trials

3

BDS 790

Dissertation Research Proposal

6

BDS 794

Journal Club

1

TOTAL TERM HOURS

13

Year 3 – Spring

BDS 794

Journal Club

1

BDS 795

Dissertation and Research Proposal II

6

Elective*

3

Elective*

3

TOTAL TERM HOURS

13

Year 4 – Summer

BDS 797 or BDS 798

Biostatistics & Data Science Internship or Dissertation Research

1

TOTAL TERM HOURS

1

Year 4 – Fall

BDS 798

Dissertation Research

1

TOTAL TERM HOURS

1

Year 4 – Spring

BDS 798

Dissertation Research

1

TOTAL TERM HOURS

1

Year 5 – Summer

BDS 797 of BDS 798

Biostatistics & Data Science Internship or Dissertation Research

1

TOTAL TERM HOURS

1

Year 5 – Fall

BDS 798

Dissertation Research

1

TOTAL TERM HOURS

1

Year 5 – Spring

BDS 798

Dissertation Research

1

TOTAL TERM HOURS

1

*Electives will be chosen from the courses offered by the Department of Data Science or other graduate degree departments upon approval of the program director.

**Students may substitute PHS 703. Epidemiology I for MSCI 710. Epidemiology I in the fall of their second year.