duke statistics phd students

G-STA-PHD - Statistical Science - PhD

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The Department of Statistical Science at Duke University offers graduate study leading to PhD and MS degrees in statistical science. The PhD program offers thorough preparation in the theory and methods of statistics, with major emphases on modern, model-based statistical science, Bayesian and classical approaches to inference, computational statistics, and machine learning. A hallmark of the program is the integration of interdisciplinary applications into teaching and research, reflecting the department’s broad and deep engagements in leadership and innovation in statistical science and its intersections with many other areas, including the biomedical sciences, computational sciences, data and information sciences, economic and policy sciences, environmental sciences, engineering, machine learning, physical sciences, and social sciences. The rich opportunities for students in interdisciplinary statistical research at Duke are complemented by opportunities for engagement in research in summer projects with nonprofit agencies, industry, and academia.

For an up-to-date faculty list and description of graduate programs in statistical science visit the website at stat.duke.edu .

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2024-2025 Graduate School Bulletin. Download PDF here.

Following the people and events that make up the research community at Duke

What does it take to be a successful PhD student? Two grad students in statistics weigh in

By Meghna Datta

On May 10, 2023

In Mathematics , Statistics , Students

With so many different career options in life, how do you know that you’ve found the right one for you?

Graduate students Edric Tam and Andrew McCormack , when asked what they hope to be doing in ten years, said they’d choose to do exactly the kind of work they’re doing right now – so clearly, they’ve found the right path. Tam, who obtained his undergraduate degree in Biomedical Engineering , Neuroscience and Applied Mathematics from Johns Hopkins University, and McCormack, who came from the University of Toronto with a degree in Statistics, are now 5 th -year PhD students in the Department of Statistical Sciences. Tam works with Professor David Dunson , while McCormack works with Professor Peter Hoff , and both hope to pursue research careers in statistics.

Research interests

For the past five years, McCormack has been doing more theoretical research, looking at how geometry can lend insights into statistical models. The example he gives is of the Fisher information matrix, a statistical model that many undergraduate statistics majors learn in their third or fourth year.

Tam, meanwhile, looks at data with unique graphical and connectivity structures that aren’t quite linear or easily modeled, such as a brain connectome or a social network. In doing so, he works on answering two questions – how can you model data like this, and how can you leverage the unique structure of the data in the process?

What both Tam and McCormack like about the field of statistics is that, as Tam puts it, “you get to play in everyone’s backyard.” Moreover, as McCormack says, the beauty of theoretical research is that, while it’s certainly more time-consuming and incremental, it is often timeless, giving insight into something previously unknown.

On walking the research path

What does it take to be a successful PhD student? Both McCormack and Tam agree that a PhD is just a degree – anyone can get one if you work hard. But what sustains both through a career in research is a passion for what they do. Tam says that “you need inherent motivation, curiosity, passion, and drive.” McCormack adds that it helps if you work on problems that are interesting to you. 

Tam, who spent some time in a biomedical engineering lab during his undergraduate years, remembers reading about math and statistics the entire time he was there, which signaled to him that maybe, biomedical engineering wasn’t for him. McCormack’s defining moment occurred in the proof-based classes he took while as an undergraduate. He initially wanted to pursue a career in finance, but he quickly became enamored by the elegant precision of mathematical proofs – “even if all you’re proving is that 1+1=2!”

“You need inherent motivation, curiosity, passion, and drive.” Edric tam, on what it takes to pursue a career in research

Even with passion for what you do, however, research can have its ups and downs. McCormack describes the rollercoaster of coming up with a new idea, convinced that “this is a paper right here”, and then a day later, after he’s had time to think about the idea, realizing that it isn’t quite up to the mark. Tam, who considers himself a pretty laidback person, sometimes finds the Type A personalities in research, as in any career field, too intense. Both McCormack and Tam prefer to not take themselves too seriously, and both exude a love for – and a trust of – the process.

Reflections on the past and the future

Upon graduation, McCormack will move to Germany to pursue a post-doc before beginning a job as Assistant Professor in Statistics at the University of Alberta. Tam will continue his research at Duke before applying to post-doc programs. In reflecting on their paths that have brought them till now, both feel content with the journey they’ve taken.

Tam sees the future in front of him – from PhD to post-doc to professorship – as “just a change in the title, with more responsibility”, and is excited to embark on his post-doc, where he gets to continue to do the research he loves. “It doesn’t get much better than this,” he laughs, and McCormack agrees. When McCormack joins the faculty at the University of Alberta, he’s looking forward to mentoring students in a much larger capacity, although he comments that the job will probably be challenging and he’s expecting to feel a little bit of imposter syndrome as he settles in.

When asked for parting thoughts, both Tam and McCormack emphasize that the best time to get into statistics and machine learning is right now. The advent of ChatGPT , for example, could replace jobs and transform education. But given their love for the field, this recommendation isn’t surprising. As Tam succinctly puts it, “given a choice between doing math and going out with friends, I would do math –  unless that friend is Andy!”

When Art and Science Meet as Equals

Shifting from social comparison to “social savoring” seems to help.

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As biomedical research becomes increasingly quantitative and complex, a need exists for individuals who possess exceptional analytic skills, a strong foundation in human biology, and the ability to effectively communicate statistical principles to multi-disciplinary research teams. Demand is particularly high for individuals formally trained in biostatistics.

Biostatisticians work as collaborative scientists, providing expertise in the statistical methods that form the evidential basis of modern biomedical research. Whether it's uncovering the genetic origins of disease, determining optimal drug therapies for patients, or studying the strategies to reduce health care costs without compromising the quality of patient care - biostatisticians engage in intellectually stimulating projects focused on the improvements of human health.

Duke University Medical Center is a world-class medical research institution that provides the ideal setting for training biostatisticians to gain exposure to state-of-the-art biostatistical methodology in the context of cutting edge science research. Our program ensures that Duke graduates are not only prepared for today's science, but will also be well-positioned to tackle tomorrow's challenges.

Duke's Master of Biostatistics Program is unique in its balanced focus on three core competencies: analysis, biology, and communication. All faculty members in the Department of Biostatistics and Bioinformatics at Duke are actively engaged in research, with projects collectively spanning a broad array of biomedical research areas. The faculty practice exactly what they teach and are dedicated to ensuring that students develop the skills and knowledge necessary to succeed as biostatisticians.

• A dynamic approach that integrates analytical skills, biological knowledge, and communication proficiency
• Early engagement with clinical and translational investigators
• Active, learner-centered curriculum
• Demonstration and practice in authentic research environments
• Those who are interested in biology, medicine, and other related fields
• Those who are comfortable with mathematics
• Those who desire to work with leading researchers in a vibrant biomedical research environment
• Those who seek to begin or further a challenging career
• Those who care about improving health

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Welcome to the ABSN Student Resources page at Duke School of Nursing! We’re committed to supporting you throughout your academic journey. Here, you’ll find a list of services and resources available both within the School of Nursing and the broader Duke community to assist you during your time here. We encourage you to utilize these resources as needed, and remember, our Office of Admissions  and Student Services  is always here to help and support you.

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What Can You Do With an Accelerated Bachelor of Science in Nursing?

An ABSN degree from Duke empowers you for a variety of diverse opportunities. According to the U.S. Bureau of Labor Statistics, registered nurses, including BSN graduates, are in high demand, with employment projected to grow by 6% through 2032.

Through the accelerated nursing program, you’ll be prepared to:

• Promote the health of diverse patients, families and communities.
• Advance nursing science by identifying questions, evaluating evidence and proposing innovative solutions to clinical practice problems.
• Provide high-quality care, health care team coordination and oversight and accountability for care delivery in various settings.
• Address health disparities in vulnerable populations, locally and globally.

Our accelerated nursing degree also provides the opportunity to earn six credits toward a future master’s degree, positioning you for a successful path to advanced nursing practice.

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Stephanie Gedzyk-Nieman DNP, MSN, NC-MNN

As assistant dean of the ABSN Program, Dr. Gedzyk-Nieman is committed to continuing the program’s high standards while also building new, innovative opportunities for practice-ready nurses of the future. Dr. Gedzyk-Nieman has been developing rewarding educational experiences for nursing students in the Childbearing Families course through a flipped classroom model and innovative, active learning strategies to reinforce concepts and enhance clinical judgment.

Learn more about Stephanie Gedzyk-Nieman:  Scholars@Duke

The Accelerated Bachelor of Science in Nursing, Master of Science in Nursing, Post-Graduate APRN Certificate and Doctor of Nursing Practice programs at Duke University School of Nursing are fully accredited by the Commission on Collegiate Nursing Education . The Nurse Anesthesia DNP program is accredited by the Council on Accreditation of Nurse Anesthesia Educational Programs .

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Duke Economics’ New Faculty Trifecta Expands Research Horizons

September 23, 2024.

Elizabeth Richardson, Trinity Communications

Three new faculty members joining  Duke Economics this fall have one important trait in common: enthusiasm for the department’s strong commitment to interdisciplinary collaboration.

Their diverse expertise will expand the department’s research capabilities, bringing new insights into areas like education and social policy, gender and labor force dynamics, and climate change policy. With a collective focus on cross-disciplinary approaches,  Michael Dinerstein ,  Alessandra González and  Felix Tintelnot will enrich the department's academic environment and foster solutions to pressing global challenges. 

Education as a Market

In graduate school, Michael Dinerstein was introduced to industrial organization, a field that examines the interaction between markets and competition. He’d always been interested in education and social policy, and he realized there was a need for more research in education economics.

“I’m bringing the study of the markets to education,” says Dinerstein, “and thinking about how schools compete for students and teachers. I look at how that competition — or lack of competition — shapes education policy.”

Dinerstein also studies development economics, which focuses on how to help developing countries improve their economic conditions. Dinerstein looks at markets in Kenya where people can buy antibiotics without a prescription. This creates a market for these drugs, which in turn creates competition between the stores that sell them. “I look at the intersection of this specific market and how it applies to health policy,” he says. 

The fact that he’s able to study several different fields within the discipline is what drew Dinerstein to Duke. “In my experience, Duke is unique in that they don’t just support collaboration, they encourage it,” he says. “That makes it an incredible place to work.”

Exploring Gender, Culture and Labor Market Dynamics

Alessandra González's research focuses on how cultural factors shape economic outcomes. She studies female labor force participation, the formation of labor market preferences and employer adaptation to cultural norms.  

Over the last decade, González has conducted research in Saudi Arabia, researching what women's economic outcomes look like there. She’s also interested in how employers adapt to the changing labor market. Her projects examine how women are being prepared for new jobs and opportunities, and how employers adapt their own organizational culture to these new female entrants. 

“As Saudi women expand into the workforce, they want what all women working with kids want, which is to have competent, affordable childcare. It’s exciting to see that becoming part of the national conversation,” González says.  

She mentions that while economists have pointed out that it's taken 100 years for women in the U.S. to find some kind of balance when it comes to work and family, that balance is still not perfectly equal.   

“In Saudi Arabia, these kinds of big changes have happened in the last 20 years,” says González. “They've doubled women's labor force participation and women have become the majority of college graduates in a short period. I investigate that quick cultural change and what it means for their economy.” 

A native Southerner, González is excited about being in North Carolina. “I went to school in the South at Rice University, which I think is very similar to Duke. They both value liberal arts education as much as research.”

“Duke draws a nice selection of students who are very motivated, but also well-rounded,” she says. “They’re open to what life brings, so I'm excited to meet some motivated students and work with them.”

Economic Influence on Global Markets and Networks

Felix Tintelnot’s research explores the impact of trade and multinational production on consumers, workers and technology.

An international trade economist, Tintelnot studies the process of globalization and how countries integrate through the exchange of goods, people, and ideas. He uses different types of data, like retail prices, tax returns from workers and companies, and business transactions to study how multinational production and trade affect prices, jobs, and the technological growth of countries. 

“It's a fascinating time to be studying something so relevant,” says Tintelnot. “You can read about the impacts of globalization in the media nearly every day.  This is an active ‘economic policy’ area, where policy decisions are constantly being made.”

For example, Tintelnot is looking at the consequences of  Buy American restrictions on consumer prices and the effectiveness of bringing electric vehicle programs to the United States. “Electric vehicles are a very tangible product, and we have access to great data in which we can observe nearly half of all car transaction prices in the United States,” he says. Using registration data, researchers like Tintelnot can also track the market share of each product over time. The current administration has selected the electric vehicle market as a target for industrial policy in the context of a legislation that was aimed to combat climate change. However, Tintelnot notes there can be a trade-off between industrial policy and environmental policy objectives, something he is excited to explore in more depth at Duke.

Tintelnot’s research also touches on related areas like industrial organization and economic geography, offering insights into how global markets and production networks are interconnected. 

Because of the interdisciplinary nature of his work, Duke was a natural fit for the economist. 

“Duke is establishing a hub of people with interest in trade and supply chains,” says Tintelnot. “It’s becoming a go-to place to study these topics. We don’t just need good people in our area, we need good people in other fields as well, and that’s what Duke is doing.”

Strengthening Partnerships

Duke Economics’ goal was to seek out a new cohort of scholars who could expand the department's research into new and exciting areas while also forming meaningful connections with the existing faculty.

“We are thrilled about Felix, Michael and Alessandra joining the department,” said Professor of Economics and department chair  James Roberts . “Each of them works at the intersection of a variety of subfields within the discipline, and as such, they will each expand our research and teaching capabilities in important and exciting ways.”

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Students Accelerate Data-Driven Climate Research through Climate+

More than 30 students participated on eight project teams in summer 2024.

This summer, students in Duke University’s Climate+ program used data science techniques to research climate challenges and potential solutions. They studied topics like saltwater intrusion, energy materials, rainfall predictions and links between climate and health.

Summer 2025 Proposals Due November 4

Duke faculty are invited to submit proposals for Climate+ projects to take place in summer 2025.  

Call for Proposals    

Climate+ offers students opportunities to take part in small research teams as a part of Duke’s 10-week Data+ summer experience. Teams of two to four undergraduate students work with a graduate student project manager and faculty leads to collect, analyze and/or visualize data to contribute to climate research. Students, who are pursuing degrees across a range of disciplines, learn to apply data science techniques like machine learning and geospatial data analysis as they undertake projects.

For summer 2024, Climate+ teams included:

• Environmental and Climate Exposures and Social Determinants of Health
• Data- and Machine Learning–Driven Analysis of Atomic Dynamics in Energy Materials
• Detecting Saltwater Intrusion in Rivers Using Remote Sensing
• Monitoring Spartina alterniflora Using Self-supervised Learning
• Duke Forest Reptile and Amphibian Data
• Energy Transition During Energy Crisis: Cape Town's Experience
• Improving Future Rainfall Predictions in the Southeastern US
• Making Climate Hazard Risk Data Useful for North Carolina Communities

Findings from this summer’s teams are already informing climate solutions. One group organized and analyzed reptile and amphibian observations in Duke Forest, providing insights that are helping forest managers monitor and protect species.

Another Climate+ team worked closely with the town of Creswell, NC , and the North Carolina Office of Recovery and Resilience to measure flood risks, developing different damage scenarios to help the town and its residents prepare for flooding impacts.

“When the students went to do on-the-ground data collection in Creswell, they got to know town leaders and some of the people who are facing flood risks,” said Robert Calderbank, director of the Rhodes Information Initiative at Duke. “People in the community were eager to partner with students around this challenge, which becomes more urgent with every heavy rain event.”

Enthusiastic about the progress of the partnership, Creswell community leaders will soon be meeting with Duke and NCORR to discuss next steps. A Bass Connections team will build on the partnership’s efforts during the 2024-2025 school year.

Since the summer 2022 launch of Climate+, more than 90 students have contributed to 21 interdisciplinary project teams spanning ecology, biology, engineering, environmental science and more.

Like all students in the broader Data+ program, Climate+ students have opportunities to learn from visiting data science professionals across numerous industries and from other student teams’ experiences and insights.

In addition, Climate+ students participate in a series of unique workshops to enhance their climate literacy, data science and interdisciplinary communication skills. Guest speakers at this year’s workshops covered topics like machine learning, data visualization, climate change science, sustainable agriculture and climate hazard risks and decision-making.

"Climate+ provides students interested in data science with opportunities to learn how these tools can help us address the causes and consequences of climate change. Over the summer, students can make meaningful progress toward climate solutions,” said Kyle Bradbury, director of the Energy Data Analytics Lab at the Nicholas Institute for Energy, Environment & Sustainability.

Climate+ is offered by the Nicholas Institute in partnership with the Rhodes Information Initiative at Duke. The program is aligned with the Duke Climate Commitment , a university-wide initiative that unites Duke’s education, research, operations and public service missions to address climate challenges. Funding for Climate+ comes from The Duke Endowment and the Rhodes Information Initiative.

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Scientific Data Manager I

Durham, NC, US, 27710

Duke University:

Duke University was created in 1924 through an indenture of trust by James Buchanan Duke. Today, Duke is regarded as one of America’s leading research universities. Located in Durham, North Carolina, Duke is positioned in the heart of the Research Triangle, which is ranked annually as one of the best places in the country to work and live. Duke has more than 15,000 students who study and conduct research in its 10 undergraduate, graduate and professional schools. With about 40,000 employees, Duke is the third largest private employer in North Carolina, and it now has international programs in more than 150 countries.

The Moffitt/Caspi research group at Duke University seeks a talented Scientific Data Manager I to facilitate research on mental health and aging.  The individual in this position will manage data used in research conducted by Professors Terrie Moffitt and Avshalom Caspi (www.moffittcaspi.com; Departments of Psychology and Neuroscience, Psychiatry and Behavioral Science, and Duke university Population Research Institute) .   The team’s work centers on two cohort studies (the NIH-funded Dunedin Longitudinal Study and the UK-MRC-funded Environmental Risk Longitudinal Twin Study), and also includes management and analysis of data from studies of human development and aging around the world. The team is small, fun, lively and productive. The team publishes cutting-edge work with high impact. 

The position primarily involves managing large longitudinal datasets: designing and maintaining electronic data directories; maintaining data integrity and documentation; and updating relevant data and scripting repositories .  The work involves working with the principal investigators; collaborating with members of the research team and researchers outside Duke University (Ph.D. students, postdoctoral fellows, statisticians, bioinformaticians) on dataset management and descriptive analyses; and co-authoring papers for publication.

The individual should be comfortable with the quantitative side of research and working directly with the data, but also needs to understand the context and purpose of what the lab does and the clientele it serves.  The desired candidate should be able to manage large datasets and also go beyond the numbers to think about how these data and studies are driving and informing policy and having an impact on the lives of those involved and beyond.

MAIN RESPONSIBILITIES

The individual in this position will work with researchers on the Duke-based team, and with collaborators at other institutions, on a variety of research projects. This includes helping the individuals identify data available to answer research questions; preparing data files (including constructing new variables); providing online rapid-response support services to co-investigators located at other institutions domestically and internationally; reviewing statistical analyses performed by other researchers on the team for accuracy; and maintaining a log of all data analysis scripts and code created by team members.  

            - Consult with students and postdocs to orient them to the labs studies.

            - Outreach to data users to help them use data appropriately.

            - Select appropriate varibles for each project.

            - Prepare data files for the PIs, trainees, and collaborators, along with documentation.

            - Create new variables as necessary using existing data.

            - Maintain scrupulous documentation of methods used in variable creation.

            - Run basic descriptive statistical analyses, prepare tables and figures.

            - Communicate with team members in biostatistics and bioinformatics to solve problems.

            - Collaborate on manuscript preparation and co-author scientific papers

             - Assist in proposal preparation for future research funding.

Data Management:

Data management activities will focus primarily, over the next couple of years, on the 50-year Dunedin Longitudinal Study. Data management activities are divided between two functions:

Working with existing data:

Devlope, monitor and anslyze data systems, evaluate their performance, discover ways to enhance them.

Data directory design and maintenance: Create & maintain web-based electronic data directory that contains documentation for data collection instruments; documentation of all available data; and descriptive statistics. The Dunedin project has over 50 years of data from psychological tests, psychiatric assessments, health interviews, and comprehensive medical examinations; a biobank; as well as brain imaging data and genetic data. The study involves millions of measurements for 1,000 individuals who have been followed intensively since their birth, for 52 years. A primary job of the Scientific Data Manager I is to redesign the electronic data dictionary of all these data into a more efficient system that enhances the experience of data users. This directory must be continually updated as new variables are created.

Recovering and restructuring archival data : The Dunedin Study data are now over 50 years old. It is sometimes necessary to go back to archival data to reconstruct variables or develop new ones. The Scientific Data Manager I will need to match what is available with what is needed, and create new variables to fit current needs. Each new variable must be carefully checked for accuracy, validity, and consistency with prior variables.

Working with new data:

- During data collection periods, monitor quality control of data collection.

- Provide feedback to data-collection staff at the research site.

- Construct new variables from the raw data, check for accuracy, document and store.

- Develop and maintain data security and backup procedures.

DESIRED QUALIFICATIONS AND SKILLS

• BA/BS or MA/MS. in Data Science, Statistics or a related computational field
• Expertise with modern databases and information system technologies
• Experience with Electronic Data Capture (EDC) systems
• Experience effectively handling large and complex datasets, including cleaning data, database management, quality control, derivation of variables, and appropriate handling of confidential information and secure data storage
• Experience working with, authoring and reviewing Standard Operating Procedures, Working Instructions and User Guides
• Expertise with R and with other statistical packages (e.g., SAS or Stata)
• Expertise in MS Office (Excel, Access, Word)
• Experience with web-design
• Exquisite attention to detail
• Ability to work independently
• Ability to multi-task and juggle competing demands
• Excellent interpersonal skills and ability to communicate effectively and clearly with both technical and non-technical teams, from undergraduates to senior researchers.
• Ability to communicate with researchers across the USA and across the world and with third party companies; must be able to write polite, clear, and grammatically correct memoranda.
• Good team player who enjoys collaborating with team members and coaching students
• Knowledge of research design
• Past record of successful multidisciplinary collaboration
• Experience with REDCap
• Experience with the implementation of CRFs and eCRFs (Case Report Forms)
• Knowledge of Good Clinical Practice (GCP), data protection regulation, and other regulatory requirements
• Experience conducting human subject research under US NIH ethics rules

Minimum Qualifications

Completion of an Associate degree in basic science, public health, clinical research or other related scientific field.

Two years of data management or research experience. A Bachelordegree may substitute for 2 years required experience.

Duke is an Affirmative Action/Equal Opportunity Employer committed to providing employment opportunity without regard to an individual's age, color, disability, gender, gender expression, gender identity, genetic information, national origin, race, religion, sex, sexual orientation, or veteran status.

Duke aspires to create a community built on collaboration, innovation, creativity, and belonging. Our collective success depends on the robust exchange of ideas—an exchange that is best when the rich diversity of our perspectives, backgrounds, and experiences flourishes. To achieve this exchange, it is essential that all members of the community feel secure and welcome, that the contributions of all individuals are respected, and that all voices are heard. All members of our community have a responsibility to uphold these values.

Essential Physical Job Functions: Certain jobs at Duke University and Duke University Health System may include essentialjob functions that require specific physical and/or mental abilities. Additional information and provision for requests for reasonable accommodation will be provided by each hiring department.

Nearest Major Market: Durham Nearest Secondary Market: Raleigh

Duke is an Affirmative Action / Equal Opportunity Employer committed to providing employment opportunity without regard to an individual’s age, color, disability, gender, gender expression, gender identity, genetic information, national origin, race, religion, sex, sexual orientation, or veteran status. Read more about Duke’s commitment to affirmative action and nondiscrimination at hr.duke.edu/eeo.

PhD in Statistics and Computer Science

PhD Program Director

PhD Administrative Assistant Angela Baldassarre  

The 4-year PhD in Statistics and Computer Science is a high profile and rigorous doctoral program, within the Department of Decision Sciences, that develops strong mathematical, statistical, computational and programming backgrounds. It arises as an expansion of the PhD in Statistics, which has been offered by the Department since 2001 and has stood out as a success story in terms of both placement and scientific achievements of its graduates.

The cross-disciplinary nature of our program is essential for gaining first-class research skills. Indeed, the rise of Machine Learning and Data Science is providing undisputed evidence that the ideal expertise for achieving new exciting advances in these areas lies at the boundaries of Statistics and Computer Science. The ability of developing both novel statistical methodologies and highly scalable computational algorithms has become crucial, due to the increasing availability of large and complex datasets.

The program is tailored to extremely talented and motivated students who wish to stand out either as statisticians having also a deep knowledge of computing, algorithms and theoretical computer science or as computer scientists with a strong training in probabilistic and statistical modeling and applications. This merging of skills is a distinctive feature of modern data scientists working on cutting-edge research topics within academic institutions, research organizations and industry. The first year will include courses that are compulsory for all enrolled PhD students and provide a common theoretical and methodological background on topics related to real analysis, probability theory and stochastic processes, theoretical computer science and computer programming, mathematical statistics. During the first year, students will choose between two tracks : Statistics and Computer Science . The second year features track-specific compulsory courses and elective courses that will be focusing on frontier research topics. The third and fourth year are devoted to the doctoral thesis.

The Faculty includes internationally acknowledged top researchers in Statistics , Computer Science , Decision Theory , Statistical Physics and Machine Learning . The program also benefits from contributions of authoritative visiting professors who deliver short monographic courses.

Following the links on the left-hand side of this page, you will be able to access full info on the program. Find out more on how to apply and the admissions process .  

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