Internship Projects

Principle Investigator: Almeria, Maria (Sonia)

Location: Human Foods Program (HFP) MOD-1, 8301 Muirkirk Road, Laurel, MD

Objective:

Project Needs and Duration:

The student should have general Microbiology knowledge and, if possible, some Molecular Biology experience. The student should have some environmental science background. The estimated duration of the internship project is one year. Time requirements include 8-10 h/week during the school year and 30 h/week during break sessions.

Description:

Cyclospora cayetanensis causes a diarrheal illness called cyclosporiasis. Outbreaks of cyclosporiasis have historically affected thousands of persons in the U.S and often occur in multi-state fashion. The outbreaks in the U.S. have been frequently linked to fresh produce. However, there are significant gaps in our knowledge of the epidemiology of C. cayetanensis, and still to date there is not a clear understanding of the relative importance of the sources and routes of transmission of C. cayetanensis infection. The potential of contaminated soil as a source of infection needs to be considered. Cyclospora oocysts are highly resistant in the environment (soil and/or water) and to chemical disinfectants, and to date there is not a clear understanding of the relative importance of the sources and routes of transmission of C. cayetanensis infection. Contact with soil has been found to be a risk factor for C. cayetanensis infection in endemic areas, such as in Peru, Guatemala, and Venezuela, as well as in an outbreak in the U.S. Furthermore, C. cayetanensis has been recently found in soil collected from under the water drippers from vegetable plots in Italy and in soil from commercial berry farms in Mexico. These data suggest that contact with soil may be an important mode of transmission and could play a role in the contamination of foods. Our group recently developed a fast and sensitive method for the detection of C. cayetanensis in soil. This method will be used in the present project for detection of the parasite in soil artificially contaminated with oocysts using the GEN1000 CONVIRON growth chambers, under controlled environmental conditions. The main objective is to determine the effects that the environmental factors (type of soil, temperature, water, humidity, and photoperiod) have in C. cayetanensis detection, and possibly survival/sporulation, in soil and herbs artificially contaminated with the parasite, and to evaluate the seasonality trends. These data will allow FDA to better understand ways of C. cayetanensis transmission and to establish control measures to disrupt the cycle of transmission. This project will also help in filling gaps in risk assessment of C. cayetanensis in soil, which to date has not been performed.

Principle Investigator: Durigan, Mauricio

Location: Human Foods Program (HFP) MOD-1, 8301 Muirkirk Road, Laurel, MD

Objective:

1. Perform detection methods like qPCR, conventional PCR, and digital PCR on the DNA extracted from environmental samples.
2. Perform the Dead-end ultrafiltration on different water sources to compare the recovery on different matrices.
3. Perform sample purification with state-of-the-art methodologies such as immune magnetic beads and/or DNA purification methodologies.
4. Contribute to data analysis using currently available bioinformatics tools.
5. Contribute to communication of the research findings by involving in preparations on posters, and manuscripts.

Project Needs and Duration:

1. The student intern should have had at least some General Microbiology courses with labs.
2. The student should have some familiarity in using computer programs other than MS office.
3. The student should have an interest to learn about PCR, qPCR and dPCR.
4. The student should be able to work in the laboratory using different kinds of sample processing, DNA preparation, spiking of samples, and microscopy.

The estimated duration of the internship project is one year. Time requirements include 8-10 h/week during the school year and 30 h/week during break sessions.

Description:

 Cyclospora cayetanensis is a protozoan parasite that causes a foodborne diarrheal illness called cyclosporiasis which is linked to the consumption of contaminated fresh produce including leafy greens, snow peas, and berries. Since 2013 there has been an increase in the number of domestically acquired laboratory-confirmed cases of cyclosporiasis. The potential use of contaminated water for agricultural purposes poses a significant public health issue to millions of people worldwide and a method for detection of C. cayetanensis in agricultural water was recently validated and published in the FDA’s BAM Chapter 19c. There is a need to evaluate the performance of this method in different water sources such as well water, produce wash water, wastewater, and surface water, among others. There is also a need to develop and apply new generation of molecular markers for detection and for genotyping in environmental samples. This study will provide FDA with tools to accumulate scientific data about the different water matrices and their impact in the transmission of C. cayetanensis.

Principle Investigator: Holt, Leighna

Location: Human Foods Program (HFP) University Station, 4300 River Road, College Park, MD

Objective:

1. Develop experience and understanding of OFCSDSI data systems (CERES, FARM, STARI, etc.) to leverage the information across these systems to collect a holistic record of the scientific information and data on food additives and food contacts.
2. Develop knowledge of various toxicology testing protocols (genetic toxicology, subchronic and chronic) to accurately capture the data and endpoints reported in toxicological study reports. This requires developing familiarity with FDA guidance and OECD test guidelines.
3. Perform specialized investigative research and provide scientific guidance and advice on subjects related to legacy data harvesting, data management, and operation of OFCSDSI data systems.
4. Evaluate the new CERES Toxicology Data Entry Tool by suggesting changes to the user interface, analyzing the current state of the tool, and identifying areas for future development.

Project Needs and Duration:

1. Awareness of basic principles of toxicology and toxicology tests (genetic toxicology, subchronic and chronic)
2. Ability to work independently
3. Experience with performing searches of databases
4. Attention to detail

The estimated duration of the internship project is one year. Time requirements include 8-10 h/week during the school year and 30 h/week during break sessions.

Description:

The intern will assist with the collection of toxicology data from OFAS legacy records for incorporation  into  the  Chemical  Evaluation  and  Risk  Estimation  System (CERES).  Updated  and  detailed  toxicology  information  in  CERES  is  used  by OFCSDSI  scientists  to  support their scientific evaluations of food additives and packaging materials through read across, filling data gaps, and computational toxicology analyses. Utilizing legacy data in this manner is in line with the 3Rs (Replacement, Reduction, and Refinement) as it reduces the need for additional testing potentially involving animal studies.

Principle Investigator: Miao Li / An Nan /, Kiara Fairman

Location: Human Foods Program (HFP) University Station, 4300 River Road, College Park, MD

Objective:

1. Add skin permeability data from publications to the database. This would include gathering skin permeability data from published literature with the assistant from generative AI tools (Llama, Claude and ChatGPT), curation of the data obtained and organization of these data into one repository. (Dr. Kiara Fairman will mentor the intern for database establishment, and Dr. Nan An will be responsible for training the intern on data curation.)
2. Identify AI/ML and/or mechanistically based models to predict skin permeability. Apply appropriate AI/ML algorithms and/or mechanistically based models for skin permeability data and compare the predictions with current models. (Drs. Miao Li and Kiara Fairman will serve as mentors to the intern to establish AI/ML and/or mechanistically based models.)

Project Needs and Duration:

1. A strong background conducting literature searches form various databases and extracting, analyzing and integrating data into tabular and narrative summaries.
2. Knowledge of at least one scripting language (e.g. Python, R, and Julia).
3. Basic knowledge of statistics, computational modeling, and AI/ML.
4. Demonstrated written and oral communications skills.

The estimated duration of the internship project is one year. Time requirements include 8-10 h/week during the school year and 30 h/week during break sessions.

Description:

Understanding dermal absorption is important for risk assessment of cosmetic ingredients. Skin permeability is a key parameter to predict the absorption and disposition of chemicals through skin into systemic circulation. A reliable prediction of skin permeability of chemicals can support the development of a physiologically based pharmacokinetic (PBPK) model after dermal exposure; which would predict an internal dose to facilitate a toxicological risk assessment. Predictive modeling of transdermal absorption started in the early 1940s. With advancements in computational modeling, different types of algorithms and models, such as Potts-Guy model, Cleek-Bunge model, Wang-Kasting-Nitsche model, etc., were reported. Compilation of a well-curated database that includes permeability data for chemicals of interest to cosmetics risk assessment would be beneficial for both research and regulatory use to create reliable predictive models for skin permeation. The Modernization of Cosmetics Regulation Act of 2022 (MoCRA) indicates the sense from Congress that animal testing should not be used for the purposes of cosmetic safety assessment (with the exception of appropriate allowances). In addition, given that animal testing is being banned in a number of jurisdictions and cosmetics are marketed internationally, it is critical that validated alternative methods are developed. Therefore, reliable and robust skin permeability data will be needed to predict the toxicity from exposure to cosmetics. A database of skin permeation data and a repository of skin permeability predictive models would support dermal exposure assessment of cosmetic ingredients and potential impurities in cosmetic products. In the 2024-2025 project, we developed a user-friendly interface for the database and commonly used predictive models for skin permeability executable locally and online (https://dermal-permeability.onrender.com/), and added key experimental parameters by reviewing in vivo and in vitro skin permeability guidances from EFSA, OECD and WHO. In the 2025-2026 project, we will focus on adding skin permeability data from publications to the database with assistance from generative artificial intelligence (AI). Additionally, we will identify AI/Machine Learning (ML) and/or mechanistically based models to predict skin permeability.

Principle Investigator: McMahon, Carrie

Location: Human Foods Program (HFP) University Station, 4300 River Road, College Park, MD

Objective:

• 1. Use and/or refine the query search terms to identify relevant news and scientific literature
  2. Establish a systematic search strategy
  3. Provide information needed for WILEE team to establish a machine learning approach
  4. Identify true/false articles provided by WILEE team
  5. Analyze data and identify new trends
  6. Summarize conclusions drawn from database
  7. Present findings to Innovative Foods Staff

Project Needs and Duration:

The applicant should have a background in biology, preferably plant science, molecular and/or cellular biology, or genetics, with an interest in agricultural biotechnology. Familiarity with searching scientific literature databases such as PubMed and strong analytical and written communication skills is also needed. Basic knowledge of MS Office (e.g., Excel), data analysis, and/or computer science is desirable. The estimated duration of the internship project is one year.

Time requirements include 8-10 h/week during the school year and 30 h/week during break sessions.

Description:

 Plant genetic engineering and genome editing are rapidly advancing, making it possible for a growing number of plant biotechnology developers to bring food crops with innovative new traits to the market. The Innovative Foods Staff in FDA’s Office of Food Chemical Safety, Dietary Supplements, and Innovation (OFCSDSI), works with developers to ensure that food from new plant varieties developed with biotechnology are safe and lawful. To be successful in their mission to protect public health while supporting scientific innovation, it is important that members of this team are prepared for future developments in the use of plant biotechnology in the food supply.

Horizon scanning is a process intended to gather information to help anticipate and prepare for future developments. This project is a horizon scanning activity that involves monitoring publicly available news and scientific literature for information about the use of plant biotechnology in plants used as food. Information about potential plant biotechnology pipeline products will be added to an internal database for future reference and to enable trend analysis.

The Innovative Foods Staff has an internal “plant biotechnology pipeline monitoring” database. This database has been updated manually by our previous and current JIFSAN Interns. To make the process more efficient, we plan to establish an automatic system through a machine learning approach by partnering with HFP’s WILEE team. The goal is to train WILEE to identify relevant news and scientific literature from publicly available databases and to extract information from those articles for populating the “plant biotechnology pipeline.” This will help OFCSDSI and the agency understand new trends, identify emerging developers, and track global developments in food and agricultural biotechnology.

Principle Investigator: Patel, Isha

Location: Human Foods Program (HFP) MOD-1, 8301 Muirkirk Road, Laurel, MD

Objective:

1. Determine limit of detection of artificially contaminated bacterial pathogens when spiked at different CFU in ready to eat produce using DNA isolated from different kits.
2. Use real time PCR to confirm the presence of the pathogen in the artificially spiked samples.

Project Needs and Duration:

1. Interns from any of the following disciplines would be desirable: microbiology, molecular biology, cell biology, and biochemistry.
2. Basic laboratory experience in microbiology/molecular biology/cell biology would be preferable.

The estimated duration of the internship project is one year. Time requirements include 8-10 h/week during the school year and 30 h/week during break sessions.

Description:

A major challenge in fresh produce associated outbreaks is to selectively enrich and detect low level foodborne pathogens accurately and rapidly. The short shelf-life of leafy greens makes source tracking difficult. Currently, established WGS methods using the Illumina MiSeq take up to 3 days to sequence and analyze the data once the isolate is selectively enriched. We propose a targeted amplification method followed by metagenomic sequencing approach using the Oxford Nanopore GridION. The GridION offers a unique, scalable sequencing approach that enables direct near real-time sequencing and an overall reduction in the time to obtain results. This is an advantage over the current Illumina based methods that take up to 2 days for the sequencing run to end. With GridION, data analysis can be performed while sequencing is in progress and therefore eliminates the need to wait for the sequencing to be completed thus saving on time. Our goal is to target and amplify pathogen specific genes to improve the detection of those pathogens present in lower amounts that may go undetected due to the abundance of microflora in metagenomic samples. If successful, the outcome of this research will be a highly sensitivity method capable of detecting low-level pathogens in leafy greens and produce. In addition, with near real-time information using the GridION, the response time and source attribution during outbreaks is expected to save at least 2 days. All this goes toward supporting FDA’s regulatory role in protecting public health.

Principle Investigator: Pava-Ripoll, Monica

Location: Human Foods Program (HFP), Wiley Building, 5001 Campus Drive, College Park, MD

Objective:

1. Perform QC on extracted genomic DNA from a variety of food products.
2. Be proficient in genomic library preparation and/or target enrichment protocols for NGS.
3. Detect amplification of target genes from insects in spiked foods using molecular methods such as PCR.
4. Socialize results of project in meetings/conferences.

Project Needs and Duration:

Students who have experience with: Genetics, genomics, laboratory experience with micropipettes, reagent preparation, etc.

The estimated duration of the internship project is one year. Time requirements include 8-10 h/week during the school year and 30 h/week during break sessions.

Description:

Developing a metagenomics method for identifying arthropods in food products.

Food products can be adulterated with insects. Insect fragments in food are currently detected by removing them from the food matrix and then quantifying and taxonomically identifying them via microscopic analysis. For regulatory purposes, both identification and quantification are pertinent because they offer details about the degree and source of insect adulteration (field pests versus storage pests, for instance). Nevertheless, taxonomical identification of the insect fragments through microscopy takes a long time and requires a high level of expertise from the analysts. It also doesn't always yield resolution down to the species level.

The study of metagenomics makes it possible to create new methods for more accurately identifying eukaryotes, like insects, in food samples. Because eucaryotic species have multiple copies of their mitochondrial DNA, metagenomics becomes extremely sensitive when paired with mitochondrial sequencing.

This project uses shotgun metagenomics to develop and validate a new method for detection and identification of insect fragments in food products. Once validated, this method will be applied in labs to identify more insects found in food and stop food that contains avoidable insect contamination from getting to consumers.

Principle Investigator: Sahu, Surasri

Location: Human Foods Program (HFP) MOD-1, 8301 Muirkirk Road, Laurel, MD

Objective:

1. Assist in the establishment and maintenance of the organ-on-a-chip system.
2. Perform/assist experiments designed to evaluate system parameters for propagation of the apicomplexan parasites.
3. Contribute to data analysis using currently available statistical analysis tools.
4. Contribute to communication of the research findings by involving in preparations on posters, and manuscripts.
5. Checking the growth/survival possibility of testing parasites in biopsy-derived organoids in-vitro and/or organ-on-chip system.
6. Develop a detection method of testing parasites using different molecular biological methods including dPCR, genome sequencing etc.
7. Develop a detection method testing organism using microscopy or imaging system.

Project Needs and Duration:

1. The student intern should have had at least some General Microbiology courses with labs.
2. The student should have some familiarity in using computer programs other than MS office.
3. Students should be able to work in the laboratory using different kinds of experimental procedures, including cell biology and molecular biology methodologies.

The estimated duration of the internship project is one year. Time requirements include 8-10 h/week during the school year and 30 h/week during break sessions.

Description:

Cyclospora cayetanensis, a microscopic intestinal parasite, causes food-borne and water-borne infections in endemic and epidemic fashion worldwide. In the US, food-borne outbreaks of C. cayetanensis have been an ongoing public health problem since mid-1990s. Current scientific knowledge suggest that this parasite is human specific, causes an intestinal disease called cyclosporiasis. Previous studies were unable to show propagation of C. cayetanensis in in vivo or in vitro systems. Also, due to the lack of animal models, the only source for oocysts for the research program to propagate C. cayetanensis in vitro, would be the oocysts obtained from patient stool samples. Scarcity of these samples renders such research impossible. To overcome this hurdle, we propose to use other related apicomplexan organisms such as Cryptosporidium spp., Toxoplasma gondii, and/or Eimeria spp., that could serve as a model for evaluating the gut-on-a-chip model, prior to testing C. cayetanensis. Cryptosporidium oocysts are the only commercially available oocysts, making these organisms amenable for starting this research projects. The organ-on-a-chip technology emulates the complexity of human gut structurally and physiologically in vitro, providing a viable research platform for challenging scientific problems such as in vitro propagation of C. cayetanensis.

Principle Investigator: Cinar, Hediye

Location: HFP MOD-1, 8301 Muirkirk Road, Laurel, MD

Objective:

1. Assist in the establishment and maintenance of the organ-on-a-chip system.
2. Perform/assist experiments designed to evaluate system parameters for propagation of the apicomplexan parasites.
3. Contribute to data analysis using currently available statistical analysis tools.
4. Contribute to communication of the research findings by involving in preparations on posters, and manuscripts.

Project Needs and Duration:

a. The student intern should have had at least some General Microbiology courses with labs.

b. The student should have some familiarity in using computer programs other than MS office.

c. Students should be able to work in the laboratory using different kinds of experimental procedures, including cell biology and molecular biology methodologies.

The estimated duration of the internship project is one year. Time requirements include 8-10 h/week during the school year and 30 h/week during break sessions.

Description:

Cyclospora cayetanensis, a microscopic intestinal parasite, causes food-borne and water-borne infections in endemic and epidemic fashion worldwide. In the US, food-borne outbreaks of C. cayetanensis have been an ongoing public health problem since mid-1990s. Current scientific knowledge suggest that this parasite is human specific, causes an intestinal disease called cyclosporiasis. Previous studies were unable to show propagation of C. cayetanensis in in vivo or in vitro systems. Also, due to the lack of animal models, the only source for oocysts for the research program to propagate C. cayetanensis in vitro, would be the oocysts obtained from patient stool samples. Scarcity of these samples renders such research impossible. To overcome this hurdle, we propose to use other related apicomplexan organisms such as Cryptosporidium spp., Toxoplasma gondii, and/or Eimeria spp., that could serve as a model for evaluating the gut-on-a-chip model, prior to testing C. cayetanensis. Cryptosporidium oocysts are the only commercially available oocysts, making these organisms amenable for starting this research projects. The organ-on-a-chip technology emulates the complexity of human gut structurally and physiologically in vitro, providing a viable research platform for challenging scientific problems such as in vitro propagation of C. cayetanensis.

Principle Investigator: Panda, Rakhi

Location: Human Foods Program (HFP), Wiley Building, 5001 Campus Drive, College Park, MD

Objective:

1. Preparation of model gluten-incurred yeast and bacteria-fermented food products such as alcoholic cider, cheese, kombucha, beer, and vinegar.
2. Analysis of gluten-incurred fermented food samples using incurred yogurt and intact gluten calibrant with the multiplex-competitive ELISA, and evaluation of the precision and accuracy of the quantitation.
3. Compare the analytical results obtained from the multiplex-competitive ELISA with other commercial competitive ELISAs for fermented/hydrolyzed gluten analysis.

Project Needs and Duration:

1. Basic pipetting skill, skills of weighing and measuring accurately, knowledge of food product preparation.
2. Courses in Analytical Chemistry and Basic Food Science is preferred but not required.

The estimated duration of the internship project is one year. Time requirements include 8-10 h/week during the school year and 30 h/week during break sessions.

Description:

Celiac disease (CD) affects approximately 1% of the world’s population and is triggered by the interaction of gluten (from wheat, rye and barley and possibly oat) with the intestinal mucosa of sensitive individuals. Currently there is no treatment available for CD, and the only option to avoid a serious reaction is to follow a lifelong gluten-free diet. Reliable and accurate quantitation of gluten in foods and ingredients is paramount to meet this goal as well as to comply with the gluten-free regulations enacted by the regulatory bodies throughout the world. Accurate quantitation of gluten in fermented or hydrolyzed foods is challenging due to the lack of appropriate calibrants and variable proteolysis. Recently, it was possible to accurately quantitate gluten in dairy products and sourdough using gluten-incurred yogurt as a calibrant with a multiplex-competitive ELISA. Further, an intact gluten calibrant has been evaluated, and the calibrant is currently being used with the multiplex-competitive ELISA to quantify gluten in dairy products and sourdough, to provide information on ppm “intact gluten equivalent” present in the fermented foods. The intern working on this project will use both the intact gluten calibrant and the incurred yogurt calibrant with the multiplex-competitive ELISA to evaluate gluten quantitation in fermented foods such as alcoholic cider, cheese, kombucha, beer, and vinegar. The intern will be involved in the preparation of gluten incurred model fermented or hydrolyzed foods, analysis of the products by the multiplex-competitive ELISA, and assist with the validation process of the method.

Principle Investigator: Pawar, Rahul

Location: Human Foods Program (HFP), Wiley Building, 5001 Campus Drive, College Park, MD

Objective:

1. Prepare analytical standards.
2. Prepare sample extracts.
3. Maintain inventory of chemical standards and products.
4. Learn daily operations of an analytical laboratory including planning experiments, assisting in sample preparation, and instrumental analysis.
5. Analyze LC-MS data and perform statistical analyses.

Project Needs and Duration:

1. Good academic standing.
2. Strong work ethic, inquisitive, pro-active, and comfortable in a laboratory environment.
3. Coursework in general and organic chemistry.
4. Interest in analytical chemistry.
5. Basic computer skills, including Excel.

The estimated duration of the internship project is one year. Time requirements include 8-10 h/week during the school year and 30 h/week during break sessions.

Description:

In the past few years, there has been a growing interest in cannabis-derived products and many diverse product formulations are available to consumers. As the cannabinoid market diversifies and emerging natural and synthetic cannabinoids gain popularity, it is critical to evolve market surveillance capabilities to understand emerging cannabinoid hemp product (CHP) market segments. Traditional approaches use targeted methods to measure concentrations of key bioactives (e.g., cannabinoids), contaminants, and impurities. However, as new formulations of CHPs are brought to the market, a method capable of recognizing all known cannabinoids and structurally related compounds is needed. In the current project, a non-targeted LC-HRMS method and molecular networking workflow will be developed to recognize natural, synthetic, and cannabinoid-derived synthetic byproducts in complex matrices, including foods and products marketed as dietary supplements. This strategy will provide the Agency with a better understanding of emerging CHPs in the current marketplace and offer a robust analytical solution to identify safety signals and inform a new regulatory framework for CHPs.

Principle Investigator: Hughes, Jamie

Location: Human Foods Program (HFP), Wiley Building, 5001 Campus Drive, College Park, MD

Objective:

The intern will:

1. Log incoming complaints
2. Monitor the review process
3. Assist with the development of revised procedures by drafting flowcharts and SOPs for the  process
4. Identify and implement automation to improve efficiency
5. Participate in meetings with stakeholders to inform and improve processes

Project Needs and Duration:

1. Experience with computer software including Power Automate, Power Apps, SharePoint, Visio, Excel and Dataverse preferred
2. Some chemistry, biology/microbiology, analytics and/or statistics coursework
3. Ability to work as part of a team

The estimated duration of the internship project is one year. Time requirements include 8-10 h/week during the school year and 30 h/week during break sessions.

Description:

HFP receives a number of complaints from industry members each year indicating concerns, potential hazards or non-compliant regulatory behaviors. The Office of Compliance (OC) plays a leadership role in managing the review and monitoring the follow-up of these complaints. OC is seeking an intern to assist with re-envisioning the review procedure, automating the process and assisting with the monitoring of complaints received.

Principle Investigator: Kwegyir-Afful, Ernest

Location: HFP University Station, 4300 River Road, College Park, MD

Objective:

The Warp Intelligent Learning Engine (WILEE) is a Division of Science and Technology initiated project to develop a data product that will provide the Office of
Food Additive Safety with an advanced data driven risked based decision-making tool. This tool will leverage AI technologies to integrate and process a large variety of
data sources, generating reports with quick insights that will significantly improve our time-to-results in predicting and analyzing market and regulatory trends that
directly affect products under the Office's regulatory purview.  At completion, WILEE will have multiple modules that enhances the Office’s capacity for
postmarket surveillance and signal detection. ​

The intern will generate a large corpus of training data that can be viewed and further refined using expert opinion from CFSAN scientists.  These refined training set(s) will be used to train WILEE’s other machine learning predictive algorithms. The project will include using an application that provides easy access to the generated training data and the ability to correctly tag the record, either affirming the prediction made by the machine learning algorithm or indicating that machine learning algorithm needs modification. The intern will also use another user interface developed to help correct misspelled names and merge common items into a single item. The results of this data preparation step will help extract toxicity data for identified substance which WILEE will use in it’s risk ranking process for identified signals.  

Project Needs and Duration:

A background in Biological Science or Chemistry is required to for the intern to be successful in this project.

The estimated duration of the internship project is one year. Time requirements include 8-10 h/week during the school year and 30 h/week during break sessions.

Description:

The intern will research and learn the FARM Data Quality utility and apply this knowledge:

1. Use the Warp Intelligent Learning Engine’s knowledge discovery interface to label signal data
2. Use data cleaning and merging tool to match name similarities for chemicals, products and pathogens.
3. Extract toxicity data for chemicals from ChemTunes