INTERDISCIPLINARY HIRING IN DATA SCIENCE, NETWORK SCIENCE, & COMPUTATIONAL NEUROSCIENCE
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UC Davis is dramatically expanding in the interrelated areas of data science, network science, and computational neuroscience.  We have been approved to hire 10+ new faculty across a range of departments and centers over a 3-year period in a variety of departments including (but not limited to) communication, computer science, ecology, physics, psychology, statistics, mathematics, and neuroscience.  Most of these positions are divided into three separate but interacting clusters: Data Science, Network Science, and Computational Neuroscience.
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Data Science Cluster
UC Davis is creating a new academic unit for Data Science, seeded with four new tenure track positions. Data Science is the process and pipeline by which we develop insights and make breakthroughs via data-driven explorations and discovery of well-framed questions. It is a new "fourth" paradigm for research and policy.

Data Science is more than advances in Computer Science, Statistics and Mathematics. These are vital ingredients that Data Science integrates differently than any one of them alone. Data Science is inherently multidisciplinary, integrative and translational.  It is broadening existing disciplines  to address qualitatively new questions, in qualitatively new ways.

We are seeking a new, less traditional type of faculty that explicitly spans multiple disciplines and not siloed or labeled by one field. We want faculty who are focused on solving important problems in different domains with novel data-driven approaches. These faculty will enable qualitatively new research across many fields by developing collaborations that provide Data Science expertise and perspectives that are needed to make the research feasible. While solving problems in specific domains, they will generalize approaches and develop new and general data science methods, techniques and tools.  The ideal candidates fall into either of two categories:
  • A PhD doing research in a core field of Data Science (e.g., Statistics, Machine Learning, Computer Science, Data Technologies, Data Visualization) whose focus is fueled by novel, advanced, challenging data-driven problems from applied domains, OR
  • A PhD in a non-Data Science field that is pioneering and evangelizing Data Science in that field (and others) and who has a very strong applied Data Science credentials.
The applications are not examples of the theory and methods, but the primary focus of the research.  Because Data Science includes the workflow and process of data-driven discovery, one of the positions is in Science and Technology Studies. This person will have a strong background in working with data for their research and will collaborate with other data scientists and domain scientists to study data science itself (its effectiveness, modes of communication and discovery, definitions of knowledge in different domains, ...)
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The faculty will work synergistically with the Data Science Initiative to explore challenging applications of Data Science, foster a broad Data Science community on campus, and engage industrial collaborators.

More information about the broad definition of Data Science at UC Davis can be found at the Data Science Initiative.  Please contact Prof. Duncan Temple Lang to discuss any questions about the positions and vision for Data Science at Davis.

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​​Network Science Cluster
UPDATE, Oct 13, 2019.

The paradigm of networks is emerging as a unifying theme across the scholarly disciplines, and at UC Davis we have tremendous strengths in empirical analysis of network data across all of our colleges, divisions, and campuses from political science to engineering to medicine. We plan to now grow our core of faculty who are focused on the foundations of network science including the mathematical theory and methodology to connect network structure with function and connect network theory with practice.  We seek faculty hires who can integrate across theory traditions in the mathematical, physical and social sciences, and who are eager to partner with our broad existing base of network practitioners to develop deep understanding of network principles, actionable insights for empirical analysis, and policy implications for our modern world composed of interconnected networks.  We have two specific target areas, each with an associated faculty hire at the Assistant or Associate Professor level:

1)
The first hire was completed in 2017 for a scholar to develop rigorous methodology for network analysis based in the Department of Environmental Science and Policy. The focus is on quantitative understanding of how social networks are linked to resilience, adaptation, governance, social sensing, and spatial and temporal networks, as they relate to agriculture, ecology and the environment. Understanding social-ecological systems is one of the most promising research frontiers, and one that intimately integrates science and policy.  Welcome Assistant Professor Tyler Scott!  

2)
The second hire was completed in 2018, for a scholar to focus on developing mathematical underpinnings of network science.  This scientist should have expertise in statistical physics of networks, graph theory, or algorithms for networks. Desired focus areas include dynamics of and on networks, phase transitions, game theoretic underpinnings, with applications to real world systems. Uncovering the mechanisms of network growth and function, resilience, adaptation and robust distributed function should enable deeper understanding of real-world networks across domains.  Welcome Professor Thilo Gross!

For more information about the Network Science hiring initiative, contact
 Raissa D'Souza.

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Computational Neuroscience Cluster
Linking the biology of the brain to the complex mental processes that define thoughts and behavior is one of the grand challenges of modern science. Advances in experimental neuroscience have led to an explosion in our ability to gather increasingly sophisticated data on brain processes at all scales. These technical advances demand new methods for the statistical analysis of the massive data sets produced by new recording techniques, and new computational models and theories to connect such measurements to circuit function and behavior. To meet this demand, UC Davis is expanding its representation in Computational Neuroscience through the hiring of 3 new tenure-track faculty positions. We seek faculty who will interact with the 80+ members of the Center for Neuroscience and the Center for Mind & Brain, and who will form an interdisciplinary cluster of researchers that individually and jointly tackles major unsolved problems in neuroscience. Specific target areas include:
 
1) Innovative methods for linking cognitive and/or affective processes to their underlying substrates. This position is joint between Psychology and Computer Science was completed in 2018.  Welcome Professor Randy O'Reilly!
 
2) Models and methods for understanding how cognition and behavior emerge from electrical and chemical signals at the molecular, cellular, circuit and/or systems levels, AND/OR  3) Identifying general principles of brain function.
     Two positions are available in the above areas.  The first was completed in 2018 and is joint between the Department of Neurobiology, Physiology, and Behavior (NPB) and the department of Mathematics.  Welcome Assistant Professor Rishi Chaudhuri!
     The second hire will occur in academic year 2020-2021.



Examples of Current Positions
This is just a sample of the positions available this year.  All currently open positions at UC Davis can be found here . Additional positions will be announced later this year and/or in subsequent years.  Important: If you would like to be considered for more than one of the open positions, please submit separate applications for each position of interest.

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