Tag Archives: competition

Finding a place to hang my lab coat

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Australia might be the land of surf, swim and sun, but something’s making all the scientists flee, says Naturejobs journalism competition winner Catherine Carnovale.

When now ex-Australian Prime Minister Tony Abbot abolished the role of science minister in September 2013, members of Australia’s scientific community fastened our seat belts. This telling sign signalled the first of many cuts to science and innovation before the new government delivered their knock-out punch to the industry in the form of the 2014-15 budget.

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{credit}Calsidyrose/Flikr{/credit}

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Five ways science communication can help you

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Naturejobs journalism competition winner Rachel Harris explains how engaging others in science has benefitted her in the lab

For the past four years I’ve been working in science communication (SciComm), and academia. I’m now mid-way through my PhD — I’m studying on Alzheimer’s disease and I know I would be finding research a lot tougher if I were not involved with science communication.

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Rachel Harris doing some SciComm at Bristol Neuroscience Festival this year

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Why don’t scientists always share their data?

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Reproducibility is the cornerstone of science, and it can be compromised by insufficient data in peer-reviewed publications. Should scientists reveal everything?

Publishing Better Science through Better Data writing competition winner Emma Vander Ende.

One of the foundations of science is its reproducibility. Without it, results are not verifiable and are therefore not believable. But even if a published result is true, there is a chance it might not be reproducible, which introduces a plethora of problems for science.

Irreproducible experiments severely limit the ability of the scientific community to build on results and advance the field. This can happen when scientists don’t share enough data, or details of their experiments in papers, and it happens quite frequently.

So why might a scientist not share their data?

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{credit}Comstock/Thinkstock{/credit}

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What are the benefits of reproducibility in science?

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There has always been an element of risk in science, which is why data must be reproducible, explains Ellen Phiddian.

On June 6, 2012, I skipped class to watch the transit of Venus. I was studying in Adelaide, Australia, where the transit lasted from early morning until mid-afternoon and we had a wonderfully sunny day to view it. If I had known a bit more about the history of the transit, I may have been more thankful for that.

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A view of Venus from over the Indian subcontinent. This photograph was taken by Japan Aerospace Exploration Agency (JAXA) astronaut Kimiya Yui from the International Space Station on December 5th, 2015

In the 1760s, astronomers made long and convoluted journeys across the globe just to observe Venus crossing the Sun. Scientists at the time wanted the transit recorded from as many continents as possible, so they could use the data to calculate the distance between the Earth and the Sun. It took years of effort and huge sums of money to orchestrate such a viewing. Continue reading →

How is the rise of data-intensive research changing what it means to be a scientist?

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Research involving vast quantities of data may be changing the image of scientific research, but is it changing the image of scientists too?

Scidata publishing better science through better data competition winner Jonathan Page.

An intrepid, khaki-clad explorer, machete in hand, cutting their way through some undiscovered wilderness. A bespectacled, grey-haired academic in a white coat, supervising some elaborate experiment in a lab, illuminated by glowing lights and flashing buttons. These are the classical images sometimes conjured when the word ‘scientist’ is mentioned.

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Horace B. Carpenter as Dr. Meirschultz, a scientist attempting to bring the dead back to life in the 1934 film Maniac

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How can better data sharing and management improve a career in science?

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Taking the time to plan how raw data will be recorded and shared can make all the difference when new research directions appear, says Matthew Edmonds.

In many research projects, there tends to be three major interested parties. The first is the researcher who actually performs the experiment and collects the data. The second is the scientist overseeing the research project, who may be collating related data from several researchers. Finally, there is the institution, which supports the research financially and provides a space in which to do it.

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{credit}Roche DG, Lanfear R, Binning SA, Haff TM, Schwanz LE, et al. (2014) Troubleshooting Public Data Archiving: Suggestions to Increase Participation. PLoS Biol 12(1): e1001779. doi:10.1371/journal.pbio.1001779, CC BY 4.0, https://commons.wikimedia.org/w/index.php?curid=30978545{/credit}

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Bonding in Boston: The importance of networking in science

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Naturejobs journalism competition winner Ashish Nair finds new hope at our Boston career expo.

A long time ago in a land galaxy far far away, there was a great gathering where those weary of the well-trodden trail of tenureships and grants repaired themselves. The gathering in question was the Naturejobs career expo, a free one-day event organized for students and scientists alike. Featuring some truly inspiring speakers, it gave a much-needed boost to my hope for a career in science that can be both emotionally and financially (yes, $$$) satisfying.

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How is the rise of data-intensive research changing what it means to be a scientist?

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Data-intensive research requires a new breed of scientist: interdisciplinary analysts who enjoy swimming in data, says Atma Ivancevic.

There has always been an emphasis on the generation of novel data in science. Being a scientist involves progressing from observation to hypothesis to experiment to output. In the past, a combination of scarce data to look at and low throughput machinery to make more has led to limited experimental outcomes.

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Atma Ivancevic

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The era of big data is coming: Scientists need to step out of their comfort zone

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As every area of research becomes data-intensive, emphasis is shifting from data generation to data analysis, bringing new challenges to researchers, says Réka Nagy.

On my first day as a new PhD student, freshly awarded molecular genetics degree in hand, I was sat down at a laptop with an unfamiliar operating system and was encouraged to explore some data using arr. What sounded like pirate speak turned out to be R, a statistical programming language. Yep – for my PhD I swapped pipettes for programming, dilutions for data and spectrophotometers for statistics. Others experienced the opposite, entering the world of biology from a computer science background.

Réka Nagy

Réka Nagy

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The beginner’s guide to the LinkedIn network

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Exploring career paths sometimes feels like coming out of a cocoon – who knows what’s out there?

Naturejobs journalism competition winner Elisa Lazzari

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{credit}Jean Branan{/credit}

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