AARI Winter Internship May 2024 on "Biofertilizers" for Loyola College - UG Students
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AARI is the first Algal Biotechnology Training and Research Institute in Chennai. AARI is equipped with a state-of-the-art bio-analytical lab. The prime focus of the institute is to develop an industrial-ready workforce as well as algal biotechnological entrepreneurs. Moreover, AARI is bridging between academia and biotechnology industries. We do research on Microbial and Molecular Biology. Our team members are being part of many industries as consultants.
Are you holding Master’s degree and looking for fully funded PhD positions? University of Copenhagen, Denmark invites online application for multiple funded PhD Programs / fully funded PhD positions in various research areas.
Candidates interested in fully funded PhD positions can check the details and may apply as soon as possible. Interested and eligible applicants may submit their online application for PhD programs via the University’s Online Application Portal.
The 3-year position is funded by the Carlsberg Semper Ardens Advance. Artificial Intelligence has made its way into our everyday life and into the sciences. With that comes great responsibility. The Center for Philosophy of Artificial Intelligence revisits the foundations of responsible Artificial Intelligence and asks deep questions about the philosophical significance of recent breakthroughs in Artificial Intelligence. The phD student is expected to work on questions relating to philosophy of Artificial Intelligence
The position will be located in the Soil Fertility research group, which focuses on soil fertility issues and environmental impacts related to sustainable agriculture with a special focus on nutrient cycling and climate change. Our research aims at a mechanistic understanding of soil nutrient and organic matter dynamics at both the level of micro-scale biogeophysical processes and at eco-system scales, in the pursuit of increased nutrient use efficiency, improved crop productivity and reduced environmental impacts from agriculture in the 21st century. The group is a part of the department of Plant and Environmental Sciences, Faculty of SCIENCE, University of Copenhagen.
The inner membrane of mitochondria, the powerhouse of the cell, is highly folded, exhibiting intricate dynamical structures called cristae that are integral to a multitude of cellular processes, in particular bioenergetic demand. Abnormal cristae architectures are associated with many diseases, such as liver dysfunction. However, it remains obscure how exactly the crista shapes emerge and are connected to molecular activities. The goal of this project is to use multiscale computer simulation to understand how the activities and cooperativity of key molecular players shape crista membranes.
We are looking for candidates within the field(s) of human computer interaction. The ideal candidate should have a strong background in user-centred research methods, with some experience of working in a research environment. We are particularly interested in candidates who have experience in formulating research questions, conducting qualitative research with diverse user groups, analysing qualitative data, and drawing design implications from user research. However, we are open to any mix of skills for an exceptional candidate. It is expected that candidates will have an M.Sc. degree in a relevant technical or social science discipline. We are particularly interested in students who have a background in the social or technical sciences but are interested in developing an interdisciplinary perspective in their future research career.
We are looking for candidates within the fields of Natural Language Processing. Applicants should hold a MSc degree or equivalent in Computer Science or a related field, and have good written and oral English skills. It is not a requirement to speak Danish or German, but — given that the project involves research with Danish and German job ad data — an advantage to have some proficiency in Danish or German. The assessment of your qualifications will also be made based on previous scientific publications (if any) and relevant work experience. The ideal candidate would have an education background, prior research or work experience in ML or NLP, as well as an interest in inter-disciplinary collaborations.
The PhD student will be tasked with the development, optimization and use of advanced methodologies for studying enzymatic activity on a single molecule level. The project will involve fluorescence imaging using TIRF, Confocal Microscopy and Lattice light sheet microscopy, single particle studies and quantitative image analysis, aiming to decipher the interaction of proteins with substrate.
Runtime monitoring is the task of identifying complex temporal patterns while incrementally processing streams of events. Tools that solve this task are called monitors. They input a temporal pattern specification, process the stream event-wise, and output verdicts that indicate for each event whether a pattern occurs at the event’s position in the stream. Some monitors use implicit specifications: they fix a particular temporal pattern and use a dedicated, optimized algorithm for the monitoring task. Other monitors support entire temporal pattern specification languages and input the specification explicitly as part of their workflow.
The goal of this PhD project is to develop and compare monitors for both implicit specifications and explicit and expressive pattern specification languages that scale to high-volume and high-velocity data streams. Implicit monitors are always tied to an application area. As a specific application, we intend to use implicit monitors to assure the correctness of an interactive proof assistant—a tool that checks formal mathematical proofs—which carries out thousands of logical inferences in what appears to its users as a single automatic proof step.
The PhD candidate will make field and/or lab-based experiments with arctic shrub species. State-of-the-art climate chambers are available for experiments. The PhD will determine key response curves for different photosynthetic processes and VOC emissions under different growth temperatures and also quantify their responses to different levels of heatwaves. The derived relationships will be directly integrated into a widely-used ecosystem model, LPJ-GUESS to assess large-scale impacts on CO2 and VOC fluxes.
The proposed project focuses on the development of tools necessary for coherent analysis of emission profiles including cross-sectorial emissions and temporal aspects of forest carbon capture and storage hitherto not combined in previous studies. With multiple pathways that forests may aid in the green transition, i.e., afforestation, setting aside of untouched forests, or managing forests for wood production and bioenergy, the proposed project centers itself in the middle of a pertinent and needed debate about the climatic consequences of forest development.
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