Research Opportunities Database

New experimental approaches based on DNA sequencing are allowing us to see where various gene regulatory processes are happening along the genome. However, these experiments produce vast amounts of data, and so turning them into an understanding of the regulatory circuitry controlling cells remains a huge challenge. The Mahony lab aims to meet this challenge by developing machine learning algorithms for detecting patterns in large regulatory genomics datasets. In particular, we focus on understanding how transcription factors and other regulatory proteins control cell behavior during development and cellular programming. We need motivated undergraduate students to help us to analyze regulatory genomics datasets and to help develop bioinformatics tools for data mining and visualizing large collections of genomics data.

Mentor: Shaun Mahony

1. data analysis and fieldwork on consumer perceptions of non-traditional foods
2. analysis of interviews, conceptual model development of agricultural cooperatives formation in Mexico
3. literature and policy analysis regarding food production, trade, advertising, and labeling, in the United States, Europe and Latin America

Mentor: Julie Stanton

CurtisLab of the Department of Chemical Engineering has a diverse array of ongoing projects that are generally quite applied and focus on realizing low-cost mechanisms to scale-up processes. A key benefit of CurtisLab is its highly interdisciplinary nature, which enables vicarious learning and a holistic approach to problem-solving and research. The processes are varied and range in focus across disciplines including:

• Molecular biology (BMB);
• Wastewater treatment (Civil/ Biochemical engineering);
• Epidemiological modeling and entomology (Entomology, Epidemiology, Chemical Engineering);
• Plant biotechnology (Plant Biology);
• Process control and interfaces (Chemical / Mechanical / Electrical Engineering);
• Mycology (Biological / Environmental Engineering)

CurtisLab heavily relies on undergraduate researchers to pursue high-risk (but high reward!!) research, encouraging them to adopt a mindset of 'fast failure' initially towards later-stage (nearly) autonomous experimentation. Over 50 honors theses have been completed in CurtisLab with many (equally-talented and dedicated) non-honors students contributing to research including (first) authorship on papers, winning poster competitions at National competitions, award of NSF graduate student fellowships, etc. With more than 400 undergraduates having worked in CurtisLab in the last 28+ years, CurtisLab alumni are throughout industry--anywhere from small startup companies (lots of biotech) to Big Ag / Big Oil / Big Pharma--and can provide a valuable network throughout one's post-baccalaureate career.

Projects anticipated to be active in the 2017-18 academic year include the following:

• African Food Security: NSF & Gates Foundation-funded project on the propagation of crops (e.g. yam, banana, cassava/tapioca) for economic and food security in Africa. This includes work with genetic engineering, protein purification, aseptic tissue culture, bioreactor design including machining, and automation (e.g. interfacing to Arduino, Raspberry Pi, soldering, etc.). 
• Scale-up of Fungus for Circadian Rhythm: Engineering promotes better science! We will be collaborating with other universities to grow the fungus, Neurospora crassa, to enable collaborators to better elucidate the model organism's circadian rhythm. This work emphasizes bioreactor operation, aseptic tissue culture, circuitry design/logic, etc. 
• Algae Biofuels (& Associated Microbiome): Characterization of algae biofuels candidates using quintessential chemical engineering principles (e.g. mixing, mass transfer, productivity analysis, stoichiometric balance, and feed-forward process control). 
• Insect Epidemiological Modeling: Includes design of an automated system for monitoring of insect fly pattern and epidemiological modeling for (insect) vector transmittance of diseases. Maker-Hacker 'types' encouraged to apply; this work will include extensive programming, circuitry logic, etc. 
• Crop improvement and Agricultural Biosecurity:  Genetic transformation of plants (and associated plant regeneration) will be the focal point of a multi-disciplinary project wherein viruses will be delivered by insects to plants towards crop improvement and agricultural biosecurity. The work will focus on genetic engineering initially and evolve towards greenhouse studies involving both plants and insects. 
• Wastewater Treatment: Scale-up of a novel process for wastewater treatment that generates fertilizer from sludge / biosolids that is energetically non-intensive and requires little capital investment. This work is critical to national wastewater treatment facilities which are currently approaching 'retirement' such that the technology demonstrated in the coming years will determine the fate of wastewater treatment (and associated taxpayer dollars) for decades to come.  
• Plant propagation for biomedical products: In collaboration with partners at PSU-Harrisburg campus, genetic engineering of a metabolic pathway will be engineered into an alternative plant for enhanced yields of biomedical product. This work will focus on genetic engineering towards later scale-up in low-cost bioreactors. 

If you are interested in any of the above projects, please apply through  http://www.curtislab.org/about/interest. More information is also available at http://www.curtislab.org/research-projects. No previous experience is required; work ethic, aptitude for steep learning curve, intensity, and excitement for exploration / dealing with uncertainty are highly-valued. 

Mentor: Wayne Curtis

Recurrent deep learning methods are changing what we can do in artificial intelligence. We are exploring problems in text, coding, and sequence understanding.

Mentor: C Lee Giles