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NASA NTRS2019

NASA Centennial Challenges Program: A Crowdsourcing Tool to Advance Life Support Technologies for Future NASA Missions

Historically, competitions and prizes such as those executed by the NASA Centennial Challenges (CC) program have created broader avenues through which to spur innovation from unlikely sources. In 2005, Congress amended the National Aeronautics and Space Act of 1958 to authorize NASA to create challenges through which prizes could be awarded to United States citizens or entities that succeeded in meeting the challenge objectives. Over the past 13 years, the CC program has initiated more than 19 challenges in a variety of technology areas, including propulsion, robotics, communications and navigation, human health, science instrumentation, nanotech, materials/structures and aerodynamics. This paper will discuss the status and the accomplishments of the CC program and discuss results of an ideation process designed to identify and formulate topics for a potential Centennial Challenge competition targeting a life support technology gap for future long-term exploration missions. Status of this challenge formulation process with information on how to use crowdsourcing tools will be discussed. An overview of the CC Program’s accomplishments, including strategic objectives, past challenges, and current challenge development and execution. This program exemplifies the values that have formed the bedrock of the culture at NASA since the beginning: innovation, imagination, and a passion for exploration.

innovation↗

NASA NTRS2019

Modeling Phenological Controls on Carbon Dynamics in Dryland Sagebrush Ecosystems

Dryland ecosystems play an important role in determining how precipitation anomalies affect terrestrial carbonfluxes at regional to global scales. Thus, to understand how climate change may affect the global carbon cycle,we must also be able to understand and model its effects on dryland vegetation. Dynamic Global VegetationModels (DGVMs) are an important tool for modeling ecosystem dynamics, but they often struggle to reproduceseasonal patterns of plant productivity. Because the phenological niche of many plant species is linked to bothtotal productivity and competitive interactions with other plants, errors in how process-based models representphenology hinder our ability to predict climate change impacts. This may be particularly problematic in drylandecosystems where many species have developed a complex phenology in response to seasonal variability in bothmoisture and temperature. Here, we examine how uncertainty in key parameters as well as the structure ofexisting phenology routines affect the ability of a DGVM to match seasonal patterns of leaf area index (LAI) andgross primary productivity (GPP) across a temperature and precipitation gradient. First, we optimized modelparameters using a combination of site-level eddy covariance data and remotely-sensed LAI data. Second, wemodified the model to include a semi-deciduous phenology type and added flexibility to the representation ofgrass phenology. While optimizing parameters reduced model bias, the largest gains in model performance wereassociated with the development of our new representation of phenology. This modified model was able to bettercapture seasonal patterns of both leaf area index (R2=0.75) and gross primary productivity (R2=0.84), thoughits ability to estimate total annual GPP depended on using eddy covariance data for optimization. The new modelalso resulted in a more realistic outcome of modeled competition between grass and shrubs. These findingsdemonstrate the importance of improving how DGVMs represent phenology in order to accurately forecastclimate change impacts in dryland ecosystems.

Ecosystem model Phenology Parameter optimization E↗

NASA NTRS2003

Laboratory for Atmospheres 2002 Technical Highlights

How can we improve our ability to predict the weather-tomorrow, next week, and into the future? How is the Earth's climate changing? What causes such change? And what are its costs? What can the atmospheres of distant planets teach us about our own planet and its evolution? The Laboratory for Atmospheres is helping to answer these and other scientific questions about our planet and its neighbors. The Laboratory conducts a broad theoretical and experimental research program studying all aspects of the atmospheres of the Earth and other planets, including their structural, dynamical, radiative, and chemical properties, with the overarching goal to provide better understanding and to improve prediction of the Earth's climate. Vigorous research is central to NASA's exploration of the frontiers of knowledge. NASA scientists play a key role in conceiving new space missions, providing mission requirements, and carrying out research to explore the behavior of planetary systems, including, notably, the Earth's. Our Laboratory's scientists also supply outside scientists with technical assistance and scientific data to further investigations not immediately addressed by NASA itself. Laboratory scientists submit competitive research proposals with diverse scientific or technological approaches to NASA and other Federal agencies to acquire research support. The Laboratory management strives to provide a working environment that promotes creativity, competition, and openness. The Laboratory for Atmospheres is a vital participant in NASA's research program. Our Laboratory often has relatively large programs, sizable satellite missions, or observational campaigns that require the cooperative and collaborative efforts of many scientists. We ensure an appropriate balance between our scientists' responsibility for these large collaborative projects and their need for an active individual research agenda. This balance allows members of the Laboratory to continuously improve their scientific credentials. The Laboratory places high importance on promoting and measuring quality in its scientific research. We strive to assure high quality through peer-review funding processes that support approximately 90% of the work in the Laboratory. The overall quality of our scientific efforts is evaluated periodically by committees of advisors from the external scientific community, as detailed in Appendix 2 of this document. Members of the Laboratory interact with the general public to support a wide range of interests in the atmospheric sciences. Among other activities, the Laboratory raises the public's awareness of atmospheric science by presenting public lectures and demonstrations, by making scientific data available to wide audiences, by teaching, and by mentoring students and teachers. Section 6 presents details of the Laboratory's outreach activities during 2002. The Laboratory is also committed to addressing the demographic imbalances that exist today in the atmospheric and space sciences. We must address these imbalances for our field to enjoy the full benefit of all of the Nation's talent. The Laboratory makes substantial efforts to attract new scientists to the fields of atmospheric and space sciences. We strongly encourage the establishment of partnerships with Federal and state agencies that have operational responsibilities to promote the societal application of Earth sciences.

Steven E. Platnick↗

NASA NTRS2018

Trusted Communication: Utilizing Speech Communication to Enhance Human-Machine Teaming Success

An area of increasing interest for the next generation of aircraft is autonomy and the integration of increasingly autonomous systems into the national airspace. Such an integration requires humans to work closely with autonomous systems, forming teams. Our hypothesis is that a team composed of both humans and autonomous systems will operate better than either entity alone. We have existing procedures for certifying pilots to operate in the national airspace and are currently working on methods for validating the function of autonomous systems, however we have no method in place for assessing the interaction of these two disparate systems. Communication is one avenue. This paper will examine the use of language as a metric for ascertaining human-machine teaming effectiveness. A proof-of-concept of the application of two communication-based analysis techniques, Linguistic Inquiry and Word Count (LIWC) and Latent Semantic Analysis (LSA), for the prediction of success in human/chatbot teaming was conducted. By running these analyses over data from the 2014 and 2015 Loebner Prize competitions of human/chatbot teaming, numerical scores were obtained that can be associated with scores provided by human judges during the competition. Correlating their LIWC and LSA data with the scores provided by the judges, and using linear regression over this correlation, formulae were obtained that predict the score of human/chatbot interaction. These formulae were tested over the 2013 Loebner Prize transcripts, determining that, though there was strong correlation between predicted and actual scores, the predictive success of this method was not strong. However, with specialized topic spaces and lexica, as well as larger data sets, the predictive power of these metrics will improve. Given the importance of providing metrics for human-machine system team success and given the promise shown by the communication-basedLIWCand LSAmethods, continuing research in this area is necessary. After examining the potential for using communication and spoken language as a metric for the success of human/autonomous system teaming, this paper then examines aspects inherent to communication systems that may contribute to unreliability and reduced trust. Modern natural language processing tools rely on deep learning algorithms to create language rules that produce accurate results, but these rules are uninterpretable. The resulting blackbox system lacks transparency necessary for full validation and complete trust. Additionally, speech-based interfaces pose other difficulties to developing coordinated teamwork between humans and autonomous systems. Human communication is infrequently limited to speech only, instead usually relying on a combination of verbal, gestural, and general body language communication. Reducing an analysis of team effectiveness to a study of spoken language alone is problematic as it leaves these other equally important forms of communication out. This paper will examine these problems and the general deficiencies in speech-based metrics for human-machine teaming.

E L Meszaros↗

NASA NTRSDate not supplied

OpenNEX: An open collaboration platform for the earth science community

Satellite data from the past several decades provide the most consistent record of land-surface processes that form the basis for scientific assessments of the impacts of climate variations and changes on the environment and human social-economical activities. During this time, scientific research on the characterization and assessment of environmental changes had tended to focus on large-scale land-surface changes with significant social-economic impacts. Increasingly, attention is shifting toward changes that occur more locally and that most directly relate to the everyday life of the majority of the population. In addition, there has been needs to develop management and policy decision support systems that are based on local environmental information. Almost at the same time, the advancement in sensor technology has allowed us to collect an unprecedented volume of environmental data. These data must be curated and analyzed to extract useful information for research and decision support purposes. Established in 2013 and funded by NASA, the Open NASA Earth eXchange (OpenNEX; https://opennex.org/ , Jia et al., 2019 ) project partnered with Amazon Web Services (AWS) to make available a large amount of Earth observing data, modeling results, and analysis tools on the AWS. OpenNEX provides researchers, developers, educators, and ordinary users with easy access to an integrated Earth science computational and data platform, enabling citizen scientists and application developers to realize the full value of NASA data assets and software tools. To encourage the public's engagement in this project, NASA ran virtual workshops and prize competitions. The virtual workshops provided online lectures and tutorials about how prominent scientists used the data in their research and the tutorials gave examples how to use the tools to interrogate the data in the Amazon cloud. Finally, the prize competitions allowed much wider participation in the OpenNEX project and enable testing the non-traditional projects and out-of-box ideas. OpenNEX has continued to evolve and mature. Here, we highlight new features and functionalities available to the community.

Jian Zhang↗

NASA NTRS2020

Kibo Robot Programming Challenge Final Activity Report

On October 8th, 2020 the Kibo Robot Programming Challenge (RPC) Finals Event took place. Student teams from Australia, Indonesia, Japan, Singapore, Taiwan, Thailand, and UAE were the finalists of the competition and became the first students to ever upload APKs to an Astrobee robot (Bumble) on the ISS. This was the culmination of a joint effort between JAXA’s Int-Ball developing team in Tsukuba, Japan and NASA’s Astrobee Facility team at NASA Ames Research Center\ in California, USA. The collaboration between JAXA and NASA started in late 2017. Throughout this time mutual visits by the engineering and management teams were organized. In July 2019 the Kibo RPC concept was formally defined and the competition started. Hundreds of students across the Asia Pacific region participated and during the final event they did so in real time with the participation of NASA’s astronaut, Chris Cassidy. Chris interacted with the students, JAXA personnel and with the robot during the activity. This report aims to summarize the lessons learned from the several crew and non-crew tended activities, the evaluations performed on ground, the coordination of resources both in the ground and at the International Space Station (ISS) as well as operations. It identifies the issues the teams faced and the solutions put in place to mitigate them.

Astrobee↗

NASA NTRS2019

Modeling Phenological Controls on Carbon Dynamics in Dryland Sagebrush Ecosystems

Dryland ecosystems play an important role in determining how precipitation anomalies affect terrestrial carbon fluxes at regional to global scales. Thus, to understand how climate change may affect the global carbon cycle, we must also be able to understand and model its effects on dryland vegetation. Dynamic Global Vegetation Models (DGVMs) are an important tool for modeling ecosystem dynamics, but they often struggle to reproduce seasonal patterns of plant productivity. Because the phenological niche of many plant species is linked to both total productivity and competitive interactions with other plants, errors in how process-based models represent phenology hinder our ability to predict climate change impacts. This may be particularly problematic in dryland ecosystems where many species have developed a complex phenology in response to seasonal variability in both moisture and temperature. Here, we examine how uncertainty in key parameters as well as the structure of existing phenology routines affect the ability of a DGVM to match seasonal patterns of leaf area index (LAI) and gross primary productivity (GPP) across a temperature and precipitation gradient. First, we optimized model parameters using a combination of site-level eddy covariance data and remotely-sensed LAI data. Second, we modified the model to include a semi-deciduous phenology type and added flexibility to the representation of grass phenology. While optimizing parameters reduced model bias, the largest gains in model performance were associated with the development of our new representation of phenology. This modified model was able to better capture seasonal patterns of both leaf area index (R(exp 2) = 0.75) and gross primary productivity (R(exp 2) = 0.84), though its ability to estimate total annual GPP depended on using eddy covariance data for optimization. The new model also resulted in a more realistic outcome of modeled competition between grass and shrubs. These findings demonstrate the importance of improving how DGVMs represent phenology in order to accurately forecast climate change impacts in dryland ecosystems.

Ecosystem model↗

NASA NTRS2020

Intellectual Property and Licensing in the Commercial Space Age

The commercial space industry is undergoing a paradigm shift from the time when governments and very large space companies dominated the industry. A confluence of laws allowing commercial space companies to operate in unprecedented ways, new technologies enabling new commercial space applications, and an influx of risk capital has drastically changed the space industry landscape. As small and medium-sized companies enter the commercial space realm, they will seek a competitive advantage, and universities and the NASA space centers are positioned to offer such advantages. The commercial space industry has recently become an active area of technology partnering and licensing, even for technologies that have experienced poor licensing performance in the past. The Jet Propulsion Laboratory is seeing unprecedented technology transfer activity in the areas of spacecraft navigation, mission design, space antennas, thrusters, radio occultation, and specialized satellites. Intellectual property rights and partnering play a crucial role in the ability of the private sector to invest in these technologies and to drive space technologies forward. Participants in this burgeoning field seek the most cutting-edge innovations to attain a competitive advantage, and it is crucial for those in the university and public sector to gain an understanding of the market forces that are driving the commercial space business.

Broderick, Daniel↗

NASA NTRS2021

Supercritical Water Oxidation (SCWO) Trade Study and 2021 Final Report

SCWO is a promising technology whose main benefits is that it is capable of completely mineralizing organic compounds in wastewater and separating inorganic salts. This means that SCWO can theoretically function as a single step water treatment system. It performs the functions of both the primary treatment system and the secondary brine drying function to achieve near 100% water recovery. It can also handle solids so no pretreatment of the feed is required. A preliminary trade study indicates that SCWO could be competitive with the ISS state of the art if its power consumption could be reduced. Thermal and mechanical energy recovery system exist that could reduce SCWO energy consumption to a level that is competitive with the state of the art. In addition, increasing the feed wastewaters organic content by including other wastes, such as feces, could produce a reactor that is thermally self-sustaining. There are 5 different types of SCWO reactors. They are; tubular, tank, impingement, transpiring wall reactors (TWR) and super critical water mixing (SCWM) reactors. Of these the best suited for NASA missions are the impingement and SCWM reactors. The impingement reactor is best suited for near term missions because it can treat the low organic content wastewaters such as are expected for initial Lunar and Mars missions and has the ability to remove precipitated inorganic solids. The SCWM reactor is best suited for longer duration CELSS type missions where high organic content wastewater is available and will resolve solids fouling and corrosion issues. In addition, these two reactors have a long NASA heritage and have been developed specifically for space flight application. Tubular reactors suffer from plugging issues which is a safety concern. Tank reactors will increase in size inversely with gravity, which will trade poorly in Lunar and Mars environments where gravity is reduced. TWR reactors require high organic content wastewater feed and the SCWM reactor is an optimized version of the TWR for NASA applications. It is recommended that in FY 2022 NASA continue to fully evaluate the ability of SCWO to produce potable water and remove inorganics as a solid byproduct. This should be done using the impingement reactor for near term missions and SCWM for longer duration missions. NASA should also develop optimized recuperative heat exchangers and pressure recovery devices to reduce power consumption and investigate inclusion of feces and other organic wastes into the wastewater model to increase its organic content and further reduce thermal energy requirements.

Supercritical Water Oxidation↗

NASA NTRS2020

Intellectual Property and Licensing in the Commercial Space Age

Broderick, Daniel↗

NASA NTRS2021

Liana optical traits increase tropical forest albedo and reduce ecosystem productivity

Lianas are a key growth form in tropical forests. Their lack of self-supporting tissues and their vertical position on top of the canopy make them strong competitors of resources. A few pioneer studies have shown that liana optical traits differ on average from those of colocated trees. Those trait discrepancies were hypothesized to be responsible for the competitive advantage of lianas over trees. Yet, in the absence of reliable modelling tools, it is impossible to unravel their impact on the forest energy balance, light competition, and on the liana success in Neotropical forests. To bridge this gap, we performed a meta-analysis of the literature to gather all published liana leaf optical spectra, as well as all canopy spectra measured over different levels of liana infestation. We then used a Bayesian data assimilation framework applied to two radiative transfer models (RTMs) covering the leaf and canopy scales to derive tropical tree and liana trait distributions, which finally informed a full dynamic vegetation model. According to the RTMs inversion, lianas grew thinner, more horizontal leaves with lower pigment concentrations. Those traits made the lianas very efficient at light interception and significantly modified the forest energy balance and its carbon cycle. While forest albedo increased by 14% in the shortwave, light availability was reduced in the understorey (−30% of the PAR radiation) and soil temperature decreased by 0.5°C. Those liana-specific traits were also responsible for a significant reduction of tree (−19%) and ecosystem (−7%) gross primary productivity (GPP) while lianas benefited from them (their GPP increased by +27%). This study provides a novel mechanistic explanation to the increase in liana abundance, new evidence of the impact of lianas on forest functioning, and paves the way for the evaluation of the large-scale impacts of lianas on forest biogeochemical cycles.

Félicien Meunier↗

NASA NTRS2022

U.S. Space-Based Earth Observations in 21 st -Century Science Diplomacy

Science diplomacy can take the form of cooperation or competition. As the global community faces new challenges, ranging from dangerous changes in Earth’s climate to increasingly coercive authoritarian regimes, civil space-based Earth observations offer the United States unique opportunities to employ science diplomacy in cooperation and competition. Investments in space-based Earth observations will be a great benefit as the United States orients itself to the diplomatic challenges of the 21st century.

Ian G. Brosnan↗

NASA NTRS2022

Modeling Demographic-Driven Vegetation Dynamics and Ecosystem Biogeochemical Cycling in NASA GISS’s Earth System Model (ModelE-BiomeE v.1.0)

We developed a demographic vegetation model, BiomeE, to improve the modeling of vegetation dynamics and ecosystem biogeochemical cycles in the NASA Goddard Institute of Space Studies' ModelE Earth system model. This model includes the processes of plant growth, mortality, reproduction, vegetation structural dynamics, and soil carbon and nitrogen storage and transformations. The model combines the plant physiological processes of ModelE's original vegetation model, Ent, with the plant demographic and ecosystem nitrogen processes that have been represented in the Geophysical Fluid Dynamics Laboratory's LM3-PPA. We used nine plant functional types to represent global natural vegetation functional diversity, including trees, shrubs, and grasses, and a new phenology model to simulate vegetation seasonal changes with temperature and precipitation fluctuations. Competition for light and soil resources is individual based, which makes the modeling of transient compositional dynamics and vegetation succession possible. Overall, the BiomeE model simulates, with fidelity comparable to other models, the dynamics of vegetation and soil biogeochemistry, including leaf area index, vegetation structure (e.g., height, tree density, size distribution, and crown organization), and ecosystem carbon and nitrogen storage and fluxes. This model allows ModelE to simulate transient and long-term biogeophysical and biogeochemical feedbacks between the climate system and land ecosystems. Furthermore, BiomeE also allows for the eco-evolutionary modeling of community assemblage in response to past and future climate changes with its individual-based competition and demographic processes.

Biogeochemical cycles↗

NASA NTRS2022

Chapter 8: Strategies for People, Partnerships, and Productivity

Multiple U.S. and international respondents defined leadership as "producing the next generation of scientists." BER could lose its international leadership irrevocably without a pipeline of the best and brightest talent to engage in the program's mission areas. Competition for this talent is international and increasingly intense between public and private institutions in rapidly emerging science and technology areas relevant to BER. The quickly evolving and highly competitive nature of ensuring next-generation scientific leadership raises important questions:

Biological and Environmental Research Advisory Com↗

NASA NTRSDate not supplied

HaloSat – A CubeSat that Studied the Hot Galactic Halo

HaloSat was the first CubeSat competitively funded by NASA's Astrophysics Division. HaloSat surveyed the sky in the soft (0.4-2 keV) band with the goal of studying diffuse X-ray emission from highly ionized oxygen in the circumgalactic medium (CGM) of the Milky Way (MW). The HaloSat science instrument (shown above ) contained three nominally identical X-ray detectors. The field of view had full response over a 10° diameter, tapering to zero response at 14° diameter. The detectors were sensitive in the 0.4-7 keV band. Typical halo spectra are shown below. The figure of merit for observing diffuse emission, survey grasp, is the product of effective area and solid angle of the field of view, AΩ. HaloSat has a small effective area, but a large field of view, giving it a grasp competitive with major missions. HaloSat’s grasp (17.6 cm 2 deg 2 at 600 eV) was larger than Chandra’s at launch (8.7 cm 2 deg 2 ). HaloSat data are archived at the HEASARC by a collaboration between NASA/MSFC, UI, and GSFC. See poster 104.01 by Jesse Bluem for details. HaloSat was built and operated by the University of Iowa (UI), NASA/GSFC, Johns Hopkins University, the Laboratoire Atmosphères, Observations Spatiales (LATMOS), and Blue Canyon Technologies.

HaloSat↗

NASA NTRS2021

Developing Compelling and Science-Focused Mission Concepts for NASA Competed Mission Proposals

Since the mid 1990s, NASA has used a competitive selection process to initiate new mission concepts. These competed missions are motivated by high-value science with low implementation and cost risks. Selectable mission concepts require highly focused science approaches—delivering high quality science “on a budget.” Prospective Principal Investigators (PIs) need to convince NASA that the science they are proposing is both compelling and has high programmatic value. Unfortunately, many of these PIs are not trained in the communication skills needed for “selling” a mission concept to stakeholders. This requires a proposal that presents an investigation in an accessible, relatable, authentic, and believable way. It is the onus of the proposing PI to convince NASA of the value of their particular science concept in a competitive environment, addressing any pre-conceived notions reviewers might have about the concept’s value, complexities, urgency, and other impediments to understanding.The importance of this can be seen in the NASA-sponsored PI Launchpad (Nov 2019 & Jun 2021)1 which was designed to help early career scientists understand the skills, methods, processes, and resources needed to develop compelling science mission concepts; as well as in JPL’s update to their concept maturity model (Jan 2020) which included the addition of Story and Strategy dimensions. This paper provides guidance to assist prospective PIs in developing compelling, science-focused mission concepts. It will provide direction for communicating concepts more clearly to make science objectives more relatable to both reviewers and a broader audience, improving the probability of selection.

Ziemer, John↗

NASA NTRSDate not supplied

NASA's Space Health Impacts for the NASA Experience (SHINE) Training Program – Space Radiation Curriculum

In February 2023, the Space Radiation Element of the NASA Human Research Program initiated a virtual, annual space radiation curriculum. The Space Health Impacts for the NASA Experience (SHINE) Space Radiation Didactic Curriculum aims to educate participants not only in the scientific aspects of space radiation but also in the agency’s risk management strategies. SHINE Space Radiation Didactic Curriculum combined weekly seminars by speakers from NASA, other government agencies, academia, and industry, with networking sessions designed to foster collaboration between the competitively selected participants as well as interactions with NASA scientists and HRP funded investigators. The inaugural course ran weekly from February 2023 to August 2023 and was comprised of lectures, less formal coffee hours, and office hours. Each two-hour seminar sessions hosted 1-3 presentations on topics which ranged from the space radiation environment to health effects and countermeasure to granting opportunities. All lectures were recorded and will be published on the THREE (The Health Risks of Extraterrestrial Environments) website for public access (https://three.jsc.nasa.gov/). As a course requirement, participants developed individual or collaborative beam time proposals for real, proposed, or potential experiments at the NASA Space Radiation Laboratory (NSRL) at the Brookhaven National Laboratory. For the 2023 course, 25 participants were selected from a total of 59 applicants. Selected participants were citizens from 8 countries and comprised 5 graduate students, 4 postdocs, 11 scientists and 5 professors/medical doctors. Participants had a wide range of expertise including molecular and cellular biology, microbiology, botany, physiology, engineering, physics, aerospace medicine, planetary science, biostatistics, and modeling. The second annual SHINE training program is scheduled from February to August 2024. In addition, a separate SHINE Space Radiation Practicum session will be held in Fall 2024 at the NSRL. The SHINE Space Radiation Practicum is a unique opportunity that has not been available to the public since the closure of the NASA Space Radiation Summer School in 2017 and will allow a small cohort of participants competitively selected in Fall 2023 to gain hands-on radiation experience.

SHINE↗

NASA NTRS2023

Increasing Diversity on Spacecraft Mission Teams Reduces Risk

Many of the NASA spacecraft sent into Earth orbit and throughout the Solar System are competitively selected and led by principal investigators (PIs). These senior scientists are responsible for directing research activities, managing the use of funds, and reporting to the funding agency. Additionally, the European Space Agency (ESA) has competitively selected missions that are led by ESA-nominated project scientists and include instruments that are overseen by PIs. Usually, the PIs and project scientists form a science working team that provides scientific leadership of the mission. These NASA and ESA PI roles require a deep understanding of the mission’s scientific goals and engineering design aspects. And, importantly, these roles also require skills in team management.

Kathleen E. Mandt↗