Science is best learned by doing, yet starting out is rarely easy. This session invites reflections on the challenges encountered during research, from forgetting a screwdriver during a field day, to not being able to compile software. Sharing challenges and their solutions is critical for Early-Career Scientists, as it can (1) lead to the development of better protocols for fieldwork, modeling, and data analysis, (2) reduce impostor syndrome while doing science, and (3) highlight the human side of science, not only in papers and conferences, but also in the people and their experiences behind them.
The goal of this session is to bring together a wide variety of experiences, stories and people. We invite submissions from any geoscientific field in two specific categories:
First, any submissions that showcase a specific problem, your Eureka moment if there was one, and your solution to it. The goal of such submissions should be to show that unforeseen problems happen to everyone, but that it is possible to overcome these. Examples may include (but are not limited to):
• Designing computing codes that run with fewer computational resources
• Using sensors, technologies, and data beyond their traditional applications
• Developing computational workflows that integrate different approaches in novel ways (e.g., machine learning, trap cameras, and social media)
• Merging methods from several disciplines into new approaches.
• Building automation methodologies that avoid errors while using high-performance computing.
Second, any submissions that provide an Early Career Perspective on the grand challenges in your specific field or the geosciences as a whole, and your proposed solutions to these. Examples may include (but are not limited to):
• Community initiatives that facilitate the use of fieldwork techniques and computational resources.
• Grand challenges framing from a perspective that highlights inclusivity, diversity, and equality.
• Community perspectives and synthesis to reduce barriers of entry in transdisciplinary paths focused on problem-solving.
• Juggling how problem-solving was applied to a research career (e.g., kids, migration)