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Agricultural and Biological Engineering

Agricultural and Biological Engineering

Available Positions

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  • Ph.D. Research Assistantship - Integrative Informatics Using AI/ML to Improve Dairy Cattle Production

    Overview: A competitive research assistantship (funded by a USDA-NIFA-FACT grant) is available jointly in the Departments of Animal Sciences (UF ANS) and Agricultural & Biological Engineering at the University of Florida (UF ABE, a major US graduate program in Biological/Agricultural Engineering) to support a doctoral student (that will enroll in either ABE or ANS) to work on projects at the interface of statistics/machine learning (ML) and smart agriculture for the dairy industry under co-advisement of Drs. Albert De Vries (PI; UF ANS) and Nikolay Bliznyuk (Co-PI; UF ABE). The research will focus on the development of new analytical and computational decision tools to improve dairy cow performance using Big Data from multiple sources (high- frequency activity data from wearable computing devices – smart collars, genetics/genomics, health biomarkers, etc) using AI/ML/statistics (including uncertainty quantification) and numerical optimization. In terms of expectations, this is a quantitative degree that will be an equivalent of a doctorate in applied AI/ML/statistics/optimization and their interface with dairy science. For a taste of applications, please view the recording from a recent UF ABE seminar talk by Dr. De Vries, available at tinyurl.com/devries-abe-2020

    Funding: conditional on satisfactory performance in coursework and research duties, this research assistantship will provide funding covering a competitive stipend, tuition, and health insurance (a standard UF waiver).

    Desired qualifications: at the very least, successful applicants will have a solid background in basic engineering mathematics (multivariate calculus, linear algebra, calculus-based probability and statistics) and scientific computing (including basic programming), as well as a keen interest in computational statistics and/or machine learning. Depending on the previous training, the admitted student may be expected to promptly gain additional technical background for research by completing coursework for a Master's degree in Statistics/Biostatistics/Data Science or AI Systems/Computer Science at UF (that will be integrated with the primary degree – the doctorate in ABE or ANS). Keen interest in Smart Agriculture (particularly, the dairy industry) is also a requirement. Previous training in natural sciences (biology, chemistry, or physics) is helpful.

    Qualified current (terminal) Master's students at UF from biostatistics, engineering, and quantitative life sciences are particularly encouraged to apply (see below; please make an inquiry prior to formally applying).

    Deadlines: This search will remain open until a suitable candidate commits to the position; UF application deadlines do not directly apply, but early applicants will have an advantage. The target time to start the assistantship is by the Fall 2021 semester (May-August 2021), although an earlier start may be possible.

    Further information is available by inquiry; please contact Dr. Bliznyuk at nbliznyuk@ufl.edu or Dr. De Vries at devries@ufl.edu (and add “USDA RA inquiry” to the subject line). Along with your inquiry, please provide (i) an up-to-date copy of your CV/resume, in pdf format, (ii) unofficial GRE scores (general test) if available (UF ABE and UF ANS no longer require GRE scores but if you have taken it, we’d like to know the results), (iii) complete transcripts from all undergraduate and graduate institutions (unofficial transcripts are acceptable when making inquiries), in pdf format, (iv) a brief statement (1-2 paragraphs) as to why you are interested in and qualified for this opportunity, and how it aligns with your future goals. Qualified candidates will be contacted separately for additional details (such as references). Please do not apply formally (or pay any fees to UF) without making the inquiry first.

  • Graduate Student - Transdisciplinary Project in collaboration with Columbia University and East Carolina University

    The University of Florida is seeking applicants to fill one graduate student position. The student will be part of a transdisciplinary project—in collaboration with Columbia University (CU) and East Carolina University (ECU)—entitled “Towards a Multi-scale Theory of Coupled Human Mobility and Environment Change.” The project aims at applying a mixed-methods approach to develop a modeling framework that integrates environmental modeling, social dynamics, and migration theories and then to use such a modeling framework to develop an integrative theory of coupled dynamics of migration and environmental change.  Some of the methods include dynamical system modeling, multilayer network approaches, climate and hydrological modeling, and Bayesian inference analyses. Different aspects of the project will be conducted across the three universities. The team will meet remotely on a regular basis and annual workshops will be held where all the team members will meet in person.

    Applicants for the graduate student positions must demonstrate a strong interest in transdisciplinary research and a Master’s degree in natural sciences, social sciences, engineering, or related/relevant fields; exceptional students with a Bachelor’s degree plus research experience in an appropriate discipline will also be considered. Persons from groups under-represented in science and engineering are encouraged to apply.

    The successful candidate should also possess some of the following qualifications: (i) strong mathematical background (especially in dynamical system and stochastic modeling); (ii) strong background in network approaches; (iii) fluency in some programming languages; (iv) skills and experience in agent-based models; and (v) open-mindedness and eagerness to learn from other disciplines. We explicitly specify the last qualification to reflect the importance of integration across disciplines in the project.

    To provide the areas of expertise involved in this project, brief descriptions of the participating faculty’s expertise are provided below.

    Rachata Muneepeerakul (Principle Investigator, UF) is a complex systems modeler. His investigative methods include dynamical system modeling, network approaches, modeling coupled natural-human systems, and modeling dispersal and evolutionary process in explicitly spatial settings.

    Michael J. Puma’s (CU) research is focused on global food security, especially understanding how susceptible the global network of food trade is to natural (e.g., megadroughts, volcanic eruptions) and man-made (e.g., wars, trade restrictions) disturbances using non-equilibrium, network-based economic models.

    Upmanu Lall’s (CU) research links climate extremes, water, food, and energy in a system modeling context. He brings expertise in Bayesian methods, systems modeling, machine learning, and spatio-temporal modeling of extremes to the project. 

    David N. Griffith (ECU) has been studying migrant populations since 1981, including work on guest workers, undocumented economic migrants, and refugees fleeing civil war, natural disasters, and collapsing states and economies.  His specific area of expertise related to this project is his work on the relationships among migration, environmental degradation, and economic development.

    Jeffrey Johnson’s (UF) work most related to this project focuses on network models of complex human and biological systems, and their integration, employing various applications of continuous-time Markov chain and exponential random graph models to the study of trophic dynamics in food webs, particularly as it relates to the interplay between food web dynamics and human behavioral networks. He has also worked on understanding the drivers of conflict, both within and between human groups.

    Rafael Muñoz-Carpena is an expert in uncertainty and global sensitivity analysis of complex models, especially complex hydrological and ecological models. His expertise in global sensitivity analysis will help determine the right level of complexity of the models.

    More information about the project can be found at

    https://abe.ufl.edu/muri-migration/

    Potential candidates should submit a CV, a cover letter, and three letters of recommendation to Dr. Rachata Muneepeerakul at rmuneepe@ufl.edu.

    The review process will start immediately. The position will likely start in Fall 2021.

  • Ph.D. Assistantship - Big Data Analytics

    A Ph.D. assistantship is available in the Agriculture & Biological Engineering Department at the University of Florida to investigate and apply strategies for enhancing the intelligence in managing various agricultural and natural resource systems using big data analytics. The tentative directions for this position will be the modeling of the spatiotemporal variance of environment monitoring information from sources including satellite and IoT networks., etc. This is an opportunity to be at the forefront of applying sophisticated data management platform and data-driven decision making in agricultural and natural resource systems.

    Ideal candidates should be highly self-motivated with a strong engineering or science background and hands-on experiences of handling real-world data. Applicants need to be comfortable with math since there will be intensive training on quantitative skills, such as programming, statistics, data science, deep learning, etc. Existing experiences in IT, AI, data science/engineering, Quality Assurance and Quality Control (QAQC) for IoT networks, and satellite data analysis are desired but not required.

    The position is available from Spring 2020~2021. Interested candidates may send a resume to Dr. Ziwen Yu, the advisor of this position, by email at ziwen.yu@ufl.edu.

  • Administrative Specialist I
    • Personnel – Responsible for the timely preparation of all personnel appointments, change orders and terminations. Maintains all personnel records for faculty and staff. Maintains all payroll records. Monitors OPS appointments to see that they do not work beyond the availability of funds. Reviews preliminary and final paylists to ensure all employees have inputted hours and are receiving correct amounts on paychecks. Develops and maintains job descriptions and organization chart for the Department, in conjunction with the Mgr, Admin Svcs. Advise supervisors on job assignments and job descriptions. Assists faculty in preparation of job descriptions and reclassification requests for faculty, USPS and TEAMS employees on grant projects. Supervises the handling of all leave records for faculty and staff. Advises on leave regulations and monitors leave use for compliance with regulations. Prepares written communications to faculty and staff regarding personnel matters. Maintains confidentiality of sensitive matters concerning disciplinary action, grievances or other personnel problems. Attends faculty meetings as resource person on personnel matters. Represents Department Chairman at other meetings concerning personnel matters. Serves as member of Department Space Committee to provide input on space and facilities needed for office staff.
    • Financial – Contacts all faculty supervisors for appropriate funding sources for grad students tuition remission. Monitors tuition expenditures of grant funds to assure that funds are expended according to contract terms; reviews LOA reports to ensure there are no budget errors and tuition follows payrolls for GA’s.
    • Travel- processes all foreign travel authorizations and expense reports. Advises all travelers on foreign travel requirements.
    • Budgetary – Processes and monitors all scholarship accounts. Processes P-card transactions as needed.
    • Serves as backup to Fiscal Asst III and receptionist, providing coverage on an as-needed basis,
    • Miscellaneous – Maintains files of administrative procedures and regulations effective department operations.
    • Assists faculty in preparation of required project outlines and research reports. Assures uniformity in meeting format guidelines. Assembles reports for transmittal to Department Chairman and appropriate Deans, including CRIS reports.
    • Administrative –General supervision is provided for OPS employees.

    Apply Online at Careers at UF

    Application Close: July 23, 2020

  • End User Computing Specialist II

    Job Description

    Diagnostics:

    Troubleshoot and resolve hardware and software issues on departmental computers.

    Software and Hardware Support:

    Install operating systems and required programs on purchased or reformatted computers. Install, update, and remove software on departmental computers. Maintain an installation log and renew software licenses. Purchase, register, and manage departmental restricted software. Update and install new programs on the ABE virtual server. Install, update, and replace hardware on departmental computers. Should be comfortable entering a chassis and be familiar with safe computer servicing practices.

    IT Security and Maintaining Network Resources:

    Resolve UF Incident Response Team alerts, which range from simple Java updates to addressing software copyright infringement. Maintain a repository of installation files and key codes of UF/departmental software. Manage private folder permissions on ABE servers, network printers, and departmental email distribution lists. Remove malicious software from departmental computers.

    General IT Support of ABE Department:

    Due to the IT needs of the department, this includes but is not limited to: completing IT ticket requests submitted via the UF/IFAS ticket system; offer videoconferencing support; generate and maintain IT service records and SOPs; upon request, train faculty and staff members on the use of fundamental programs, Windows, Microsoft Office Suite, and internet browsers; update website contact information, links, and images; and other IT support tasks as needed.

    Preferred Qualifications:

    • Knowledge of IT concepts, terminology, principles, and analytical techniques.
    • Skills in programming with computer software.
    • Skills in management and administration of Window and Linux Operating Systems.
    • Ability to establish and maintain effective working relationships with others.
    • Ability to analyze and interpret data obtained while troubleshooting problems and respond with appropriate action.
    • Ability to plan, organize, and coordinate work assignments.
    • Ability to communicate computer-related information effectively, verbally and in writing.

    Apply Online with Careers at UF

    Applications Close: July 21, 2020

  • Ph.D. Research Assistantship - Quantitative Mitigation of Pesticides with Vegetative Filter Strips

    Expression of Interest for a Doctoral Fellowship candidate, Spring or Fall 2021

    Fate of Vegetative Filter Strips Pesticide Residue Between Runoff Events for Quantitative Pesticide Mitigation in Regulatory Environmental Assessments with VFSMOD

    We are interested on recruiting a suitable candidate for an exciting cutting-edge research opportunity at UF Agricultural and Biological Engineering. We are seeking a candidate with excellent quantitative and experimental skills at the laboratory mesoscale, or interest and ability to developing these.

    The aim of the research project is to experimentally and numerically verify the assumptions and accuracy of a new comprehensive pesticide residue component within VFSMOD in the context of continuous, long-term pesticide regulatory exposure assessments. Regulatory exposure assessments (EA) are a cornerstone in the registration of new or existing agrochemicals in the USA and many other countries to preserve ecosystem health and water quality.  VFSMOD (Muñoz-Carpena et al., 1999; 2004) is a numerical, storm-based design model that quantifies the performance of vegetative filter strips- VFS (grass buffers) to mitigate pesticide runoff into surface waters. During the rainfall-runoff event it calculates the hydrological and transport processes (sediment, pesticides, reactive solutes) occurring in the VFS based on initial conditions (soil water, vegetation) and boundary conditions (rainfall, inflow runoff from the field). The model has been coupled into current USA and EU long-term (20 to 30 yr), higher-tier regulatory pesticide EAs to estimate potential pesticide load reductions before entering the aquatic environment. Long-term simulations require realistic initial conditions at the beginning of each runoff event in the time series (initial soil water, pesticide residue and vegetation status).

    A new comprehensive modeling component has been added to VFSMOD to quantify the fate VFS pesticides residue between events in the context of long-term simulations. To test the new component, it is necessary to obtain detailed experimental data that tracks the VFS residues in the surface of the soil, water and vegetation compartments during consecutive runoff events. In this proposal, a combination of controlled laboratory experiments at the mesoscale is presented to obtain a comprehensive dataset to test and refine the conceptual assumptions of the new residue component. The results of the experiments will be used to test VFSMOD using state-of-the-art, parametrization and model evaluation techniques, and to further document and support the model for use in long-term EAs. The project will offer unique opportunities to interact with government and industry partners.

    We strongly encourage qualified applicants from diverse backgrounds to apply. Please send your Expression of Interest with the materials described above by email to Dr. Rafael Muñoz-Carpena, Professor in Hydrology and Water Quality, UF Agricultural and Biological Engineering, email: carpena@ufl.edu

  • Postdoctoral Associate - Modeling and Process Control

    Position Description:

    The Controlled Environment Agricultural (CEA) Group in the Department of Agricultural and Biological Engineering at the University of Florida has an opening for a postdoc position for two years in the area of modeling and optimization of sustainable environmental-agricultural systems. This project is supported by an NSF-CPS (cyber physics system) grant funded through the USDA and the candidate will have the great opportunity to collaborate with a multidisciplary team. The position is related to the modeling and optimization of technology-driven CEA systems that can achieve energy saving, and food and nutrient security. The ideal candidate should have expertise in one or more of the following areas: 1) dynamic process modeling (data-driven), 2) advanced process control and optimization, 3) machine-learning algorithms or time-series analysis, and 4) modeling and analysis of crop phenotypic information.

    Location: University of Florida, Department of Agricultural and Biological Engineering, Gainesville, Florida, USA

    Qualifications:

    1. A Ph.D. degree in chemical, industrial or agricultural system engineering with excellent computation, data analysis and modeling background
    2. Strong publication record
    3. Excellent academic writing and presentation skills
    4. Team player who enjoys supervising PhD or Master students in interdisciplinary areas among chemical engineering, environmental, agricultural and industrial engineering
    5. Experience to manage/maintain a wet chemistry laboratory is a plus

    Please send your CV and/or one-page research plan or statement to ztong@ufl.edu.

  • Ph.D. Research Assistantship - Precision Irrigation and UAV-based Crop Phenotyping

    Position Description

    The overarching goal of this project is to develop effective strategies for the implementation of precision irrigation management practices that will not only conserve freshwater resources and increase crop yield but also improve water quality and ensure environmental sustainability. This project aims to develop a method that will be used for quantifying field scale actual evapotranspiration rates and crop water stress levels by integrating data from ground measurements, Unmanned Aerial Vehicles (UAVs), and modeling. This is a collaborative project that brings together a diverse team of multi-disciplinary scientists and the student will have an exciting opportunity to engage and collaborate on different topics relevant to the project.

    Anticipated start date: Spring 2021

    Deadline: Applications will be accepted until the position is filled.

  • Ph.D. Research Assistantship - Hydrology, Saltwater Intrusion, and Soil Health

    Position Description

    Salinity due to saltwater intrusion (SWI) will impact soil health and agricultural production. As such the significant threats of salinity necessitate more work to better understand its impacts on soil health indicator parameters and associated functional ecosystem processes. This is even of greater importance in areas, such as South Florida, where the surface and groundwater resources are hydrologically connected due to the shallow and highly permeable limestone soils. This research will employ multi-pronged approaches  to investigate the multifaceted impacts of SWI on soil hydrology and bio-physicochemical properties, greenhouse gas emission & nutrient leaching from agricultural soils. The project will also test potentials of different soil management strategies to mitigate the negative effects of SWI. This is a collaborative project that brings together a diverse team of multi-disciplinary scientists.

    Anticipated start date: Spring 2021

    Deadline: Applications will be accepted until the position is filled.

  • Postdoctoral - Agricultural Engineering (Automation and Robotics)

    Postdoctoral of Agricultural Engineering (Automation and Robotics)

    The Southwest Florida Research and Education Center (SWFREC) is looking for a motivated individual to join the precision ag. engineering team (https://twitter.com/PrecAgSWFREC) as post- doctoral under the supervision of Dr. Yiannis Ampatzidis at University of Florida (Department of Agricultural and Biological Engineering). The postdoc will support engineering activities such as design, test, verification, modification, fabrication and assembly of prototype mechatronic systems. The selected candidate will work in the area of artificial intelligence (AI), mechatronics, machine vision (e.g. disease detection, yield estimation), robotics (including UAVs) and precision farming technologies. Primary responsibilities include developing automated and robotic systems for agricultural applications, designing and implementing research studies, collecting and analyzing data, and assisting the engineering team in preparing research results for publication. Applicants should have excellent verbal and written communication skills and be available for an interview (for questions contact Dr. Ampatzidis at i.ampatzidis@ufl.edu).