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Assistant Professor-Public Health Data Science-Berkeley School of Public Health



Assistant Professor-Public Health Data Science-Berkeley School of Public Health

The University of California, Berkeley seeks applicants for a tenure track (Assistant Professor) position in the area of Public Health Data Science. The successful candidate will be invited to join the Division of Biostatistics in the UC Berkeley School of Public Health, as well as the Interdepartmental Graduate Group in Biostatistics, which includes faculty from the Statistics, Electrical Engineering and Computer Science, Education, Computational Biology, and other programs on the larger Berkeley campus.

We aim to recruit an Assistant Professor with exceptional promise for pathbreaking contributions in research and education in public health data science (https://publichealth.berkeley.edu/academics/biostatistics/). Advances in data science in the coming decade will fundamentally transform the work of healthcare and public health. Biostatistics at UC Berkeley is a world leader in the fields of causal inference, machine learning, precision medicine, and high dimensional neuroscience data, among others. Hallmarks of our program include the breadth and depth of our high profile collaborative health research, and cutting-edge theoretical work on the asymptotics of estimation procedures using machine learning. We also maintain close connections with the Division of Computing, Data Science, and Society (https://data.berkeley.edu/), and with the health sciences at UCSF, providing an unprecedented opportunity for multidisciplinary collaboration at the intersection of statistics and data science, computing and health science.

This is designed to be a broad search at the intersection of data science and public health. The specific areas of interest within public health data science are not restricted, and may include expertise in big data analytics, precision public health and medicine, clinical decision support, electronic health records, exposomics, genomics, health informatics, interoperability, algorithms, machine learning, mHealth, networks, privacy, and related areas. We welcome applicants with training in biostatistics, statistics and/or relevant fields including computational biology, computer science, data science, economics, health services research, or information sciences. Regardless of discipline, the successful candidate will have training in biostatistical methods and theory crucial to meeting key graduate-level teaching and advising roles within the school, including statistical estimation and inference in large non-parametric and semiparametric models. Preference will be given to applicants who bring a strong background in theory or applications of machine learning and statistics to causal inference problems.

Diversity, equity, inclusion and belonging are core values of UC Berkeley. Our excellence can only be fully realized by faculty, students, and staff who share our commitment to these values, particularly those of anti-racism. We are particularly interested in scholars with a commitment and track record of promoting diversity, equity, inclusion and belonging in the realms of research, teaching, and/or service. At Berkeley, we recognize the intrinsic relationship between diversity and excellence in all our endeavors and embrace open and equitable access to opportunities for learning and development as our obligation and goal. The Bay Area is also at the forefront of social and health equity innovation and justice. We are committed to creating an anti-racist culture that promotes and values diversity in racial, gender, sexual, and other identities. The School of Public Health is committed to addressing the family needs of faculty, including dual career couples and single parents. We are also interested in candidates who have had non-traditional career paths or who have taken time off for family reasons, or who have achieved excellence in careers outside academia.

For information about potential relocation to Berkeley, or career needs of accompanying partners and spouses, please visit: http://ofew.berkeley.edu/new-faculty.


To apply, visit https://aprecruit.berkeley.edu/JPF03139







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