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Category Archives: Career

End of freelancing as scientist (for now)

The patchwork landscape of Masuria
Image via Wikipedia

Almost a year ago I wrote a post about officially becoming “freelance scientist”. I didn’t really know what I was doing, but taking over the world from a small flat in the middle of nowhere in Poland sounded like a good idea. And it definitely was a good idea, however not in a way I thought it would be. Today I am hoping that all things will go fine and I’ll be employed since February in a calm academic environment.

What I aimed for?

My plan was to become freelance scientist – to be able to thrive financially and intelectually without relying on gaming grant systems. I had hoped to secure support from private sources, form a virtual institute and live happily in the middle of nowhere while still having an impact on the world’s science, possibly all under “open research” badge.

What didn’t work?

Side comment: if you read excellent piece by Hugh MacLeod entitled “How to be creative”, you shouldn’t find the issues below surprising :).

The main reason I started to look for a job already some weeks ago was that freelancing as a scientist turned out to be unsustainable financially. And don’t get me wrong – money wasn’t an issue, as long as I was willing to put all my time into other’s people projects. All. My. Time. Booking some time to work on my own ideas meant burning savings at a quick rate. But I had to work on my own ideas. I didn’t feel like I’m learning very much, because I worked on things I was already quite good at. Intellectual stretching was not that big.

Because of the issue above, I’ve put together far less work than I aimed to. I have lots of posts, manuscripts and presentations which I didn’t have time to finish. I was too busy doing freelance work, finishing the projects I had promised to do, inventing new projects and hiding under a bed worrying about where this is all going.

Working in the middle of nowhere was a plain mistake. It sounds nice, but f2f networking (“showing up”) is far more important than I’ve thought. Working in Poland is an issue on its own (no matter if you’re a freelancing or an academic scientist); working outside of any major city makes it even worse.

Partially connected to the former issue was the fact that I tried to do all things alone. Wrong. Very wrong. Things like virtual institute will not work, unless there’s a team. Period.

And finally, I didn’t give myself enough time to make the whole system work. It turned out that I had no idea about so many things influencing money-flow in the system, that it’s not surprising at all that it didn’t click in so short (12 months) time.

What worked?

One of two biggest advantages of this crazy 12 months was that it was a great learning experience. When I look at my older colleagues working in academic environment, I’m pretty sure they don’t experience “felling like an idiot” moments all that often. Such moments happen quite frequently in grad school, but seem to become rarer the further science career advances. On a contrary, I had such moments all the time in the last year. I was experimenting with blog posts, stupid ideas, unbalanced opinions and I was scared as hell each time. And I have learnt much more than I would do playing safe. Have you watched Ken Robinson’s talk at TED? He put a beatiful phrase – “prepared to be wrong”. Keep that in mind.

People were second most important factor here. I was amazed by a number of people that have helped me along the way. Lots of them have encouraged me, pointed to useful resources or invested significant amount of time into answering my silly questions. Many times I was blown away by the help I had not expected. Biogang/Life Scientists community rules.

Frequently quoted phrase from Bill Hooker’s essay, “I’ve never had an idea that couldn’t be improved by sharing it with as many people as possible — and I don’t think anyone else has, either.”, turned out to be absolutely true. Each time I presented my ideas, people were interacting with them, not judging them. I was given suggestions I would not come up with by myself, even if it was clear that we’re not going to do business together.

What now?

The job I hope to land next year is going to address the things I’ve written about above. I hope to have some financial stability and necessary time to advance my plans. It will also provide a support for such events like “Startup weekend in science”, which I plan to invite you all later next year.

The main goal is still valid and I don’t give up on it. I’ve found (or rather the other way round) a real-life example, ProTech Institute from Lithuania, which means that it can be done – it’s just a little harder if you’re a (still,  but not for long) PhD student.

So it’s end of freelancing for now. Lessons learned. Back to real-life™ again :).

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Posted by on December 9, 2008 in Career, Comments

 

Photography is not a hobby. Updated CV and feedback request.

Visual resumeYesterday I asked over at FriendFeed for the feedback on my early attempt of making visual CV (big thanks to all who commented). Here’s a revised version that hopefully looks much better. The key to read the image above (click to see larger version) is as follows: Y-axis represents time (with dotted line indicating more or less the present moment); areas of interest are along X-axis; color of the phrases indicates my confidence level; font size denotes amount of time I spent on the topic (so in this case I have spent lots of time using perl, but I still don’t feel very confident about it); placement of the phrases denotes which areas of interest particular project/phrase spans; area below the dotted line shows my approximate plans and hopes for the future.

The first version had “Photography” area instead of “Visualization”, but I needed to change that since it was confusing everybody and raised questions why I put a hobby on a professional CV. Photography (or visual arts) is not my hobby. My hobby is choir singing (which I do for over 14 years already, currently singing jazz and gospel). Visualization/Photography is there to indicate that I consider data visualization one of the most important elements of scientific method. What I’m trying to figure out is what kind of presentation can help us in understanding really complex systems, such as human (genetic, to make it easier) diseases. And when we understand them curing is going to be much easier. At least I hope it will.

Anyway, the true reason to post it is to ask my readers for feedback on missing elements of my plans. So far my ideas for the future research projects split into a few paths. First path is to work further on bacterial systems (or subsystems, such as secretion systems etc.). This work would translate later on into something I call Synthetic Biology Framework, which would be a tool helping in designing new biological systems, and maybe later would result in creating a programming language for a cell. My first ideas about the framework were to design engineered bacteria producing some important compounds, maybe drugs, but now I think the cooler use for the framework would be to design bionano machines. The second path is about modelling of human diseases, with important milestone which is analysis of human genome and metagenome (genobiome as I call it) – if the data will be available. Because I don’t think I could do better here than thousands of scientists if I were using the same information, here’s a moment where synthetic biology comes into play again – I hope that I could design nanomachines that would server as quick diagnostic tools or would be reporting the body state in some mostly non-invasive way (aiming at issue of “how is my cholesterol level building up”). The third path is mostly empty and concerns visualization methods. So far I have no clear idea how to build a system that would visually assist in understanding how cells work. I plan to experiment with 3D printing and 3D visualization of biological networks, but I have no clear idea where this will lead me.

So if you have some opinion, comment, idea how to connect some dots, how to jump from one area to another (for example I have no yet idea how to approach pharmacogenomics), or if you think that it doesn’t make sense at all feel free to comment.

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Posted by on November 18, 2008 in Career, Research

 

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Data from Bioinformatics Career Survey posted

Data analysis of Bioinformatics Career Survey

Data analysis of Bioinformatics Career Survey

Michael Barton did a great job of collecting and cleaning data for First Bioinformatics Career Survey. Raw results are available at Github and please read also details on the analysis and sharing results over at OWW page.

Michael encouraged to go wild with an analysis, so here’s my quick look at the data. On the image above you can see a scatter plot of salary vs years in the field (top), histogram of salaries (bottom left), histogram of planned years in the field and histogram of positions (bottom right). All plots are colored according to the positions.

There some obvious things in these graphs, such as correlations between position and salary or between years in the field and position (see also the video below). But what strikes me is the plot showing estimated number of years in the field. There are some local maxima at around 5, 20 and 30 years, but its very interesting to see that ca. half of the people see themselves in bioinformatics for another 25-30 years and longer, and there’s no clear correlation between positions of these people and these predictions (other than senior/PI-level staff doesn’t like an idea of working for another 30-40 years). The reason I find it interesting is that I have no idea how bioinformatics will look like in these 20-30 years (and that was the reason I’ve put conservative 5 years in this field). Do you know? Do you have an idea how bioinformatics will look like so much time ahead?

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Posted by on September 2, 2008 in bioinformatics, Career

 

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One year of blogging – plans for ten years

Ethos Roundtable at Bob Doyle's Home - July 18...Image by Pathfinder Linden via Flickr

Following BioBarCamp I missed one year anniversary of this blog. With sixty something posts I cannot say I’m very productive blogger, but I didn’t aim at being one, as probably all other science-types. My goal was to be engaged in the conversation and I have reached it much faster than I expected. I got lots of help and encouragement from people I wouldn’t even dear to email a year ago. I know much more than I did on things outside of my research area. While it sounds all pathetic, advantages of being part of this community are hard to overestimate – I wrote about it couple of times already (and Neils did a great job summarizing why you should have a web presence).

Where is “Freelancing science” heading? That’s a question I asked myself pretty often during last 12 months. At first, I just blogged about interesting stuff around bioinformatics. Then I made a jump into freelancing as scientists (and this experiment goes pretty well). Statistics on keywords people are using to find this blog clearly show that there’s some interest within bioinformatics community in following this path. But the idea for this blog I have right now is not about freelancing anymore. Or rather it’s about freelancing on the next level, because today I think about starting a non-profit institute.

I believe that small research groups formed as a non-profit organizations will have enourmous impact on science within next ten, twenty years (more about it in upcoming post about the future of scientists). In spirit of freelancing they will jump from one project to another (see Deepak’s post about bursty work and follow-ups), developing solutions and making discoveries much faster (or cheaper) than it is possible in beaurocratic environment. We do have tools for effective collaboration online, we have new generation scientists that do not feel attached to academic system and we have science which starts to evolve about undestanding data, not performing experiments. Is it time to try such approach?

So, watch this space to see how the idea develops. I’m also interested in your opinions and experiences with starting and cooperating with non-profits if you have any.

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Posted by on August 11, 2008 in Career, Community, Research

 

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By any measure I’m average at most

Nature, Science and PNASImage via Wikipedia

As you have probably noticed, yesterday’s BioBarCamp was covered in depth over at FriendFeed and additionally Cameron was streaming video live from the event (it’s still available under the same address). One particular session drawed my attention, because it was about measuring impact of scientists. It’s something I have very strong opinion about since couple of weeks, so forgive me this rant.

Peter Binfield (PLoS) and Pedro Beltrao did a great job on presenting current status of the issue and presented potential way to measure impact of a publication (quoting after Shirley“your article received x citations, viewed x times, received x comments, bookmarked x times, rated x by experts, discussed on x respected blogs, appeared in x news media, etc etc” – instead of single “your article was published in journal with IF of X”). And while two months ago I was really interested in such discussions and willing to help, today I simply don’t care. The reason is simple and is presented in the post title: by any measure, I’m average at most.

That’s absolutely obvious that majority of scientists is at most average by any standard or measure. And that is not going to change, at least not much. Those who are at the top by Impact Factor today, will be at the top by other measure. Those who do some not-that-important stuff like me, will be still pretty average by other measure. One of the reasons may be all kinds of issues with normalization of the field size (there’s too much problems with biological ontologies to believe that dividing science space into fields is going to work much better). Another thing may be relative importance of the field (that’s something different from field size) – human research will always draw more attention than electrochemistry. And I could go on and on – all these issues aren’t novel and have been described and discussed in thousands of blog posts. The point is that even if such new ideal measure is going to be fair, it will not change life of majority of scientists. Not only because some of us do average things, but also because some of us have average money (BTW, I haven’t found much discussion on including in the measure research budget, which surprises me given the fact that amount of money spent on a project correlates pretty much with the IF of the journal it is published in afterwards).

So, I don’t really care if IF stays or not (although people working on improving measuring get my deep respect). Reputation-wise I’m going to be in the middle unless I will make something extraordinary. But honestly to make a scientific breakthrough the last thing I need is a number describing quality of my thinking.

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Posted by on August 8, 2008 in Career, Comments, Research

 

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Growing in open source business model

cleanedImage by *w* via Flickr

Last couple of months I’ve been quite busy with writing PhD thesis and few other projects, but also I was trying to start an open project balancing between academia and industry. This balance sounds like an opportunity, but in fact it was an issue instead. The issue wasn’t in the money – I was lucky to find people willing to help me in getting funding. The issue was rather in what I need to give away in exchange for the money – openness, control over the project or all intellectual property rights. Being already established scientist or a business person would solve such issues immediately, but I am still PhD student, so I need to face it. And while I have still plenty of people to talk to (I think it will take another month or two), that left me thinking about career on the border between industry and academia.

On both sides, in academia and industry, career path (and I’m not talking here only about having a job, but also about starting a business by yourself) is somehow clear and one can get a significant help along the way, but I haven’t found such clear path on the border between these two. Open source business model seems to work well mostly for very established players (such as Apache or RedHat) – growing in such model looks much more difficult than on either of sides. Probably Antony Williams from ChemSpider (who was one of the people that inspired and encouraged me to follow this path) would say much more in here, especially how easy (is not) to get a financial support for working on a project like ChemSpider.

I don’t think about working in one or the other environment anymore. Being freelancing scientist has a lot of good sides and growing wouldn’t be an issue (for example I have enough collaborations and ideas to cover financially next 3-4 years from grants; publications would follow). But, as I wrote before,some of the projects I’d love to work on are unlikely to be funded in academic system. On the other hand, openness is too important for me to give it away, so only a merger of these two sounds interesting. There are few examples of successful merging industry and academia, but they all seem to operate on different principles, compared to my recent attempts. Craig Venter’s model was as far as I know most of the time double-sided – he had a non-profit search unit and a company that commercialized its discoveries. Pretty similar has also David E. Shaw. So I have started to wonder if sticking to borderline is actually the very best idea. Being involved on two fronts at the same time sounds pretty overwhelming, but so far these are the only examples when this whole idea seems to work. Are you aware of any others?

My other hope is that new ways of growing on the borderline will very soon emerge. There’s quite a lot happening right now on the front of supporting innovations (including open models), so maybe over there I will find my niche. We’ll see.

(The image above is not my desk. While I work in a home office, mine doesn’t look so clean.)

Further reading:

A microfunding system for research and innovation.

Pharma looks at new ways of innovate.

Discussion around business model around Open Data is building up.

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Posted by on July 21, 2008 in Career, Comments, Research

 

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Freelancing science – today and tomorrow

In response to recent Neil’s comment and questions that repeat in emails, I’ve decided to describe in little more detail my status as a freelancing scientist. However keep in mind that I have no idea about such arrangement outside of Poland, so it is likely that some things may look different in other countries.

First of all, I need to explain my unemployment: I have a academic affiliation, but I’m not formally employed and I don’t get a salary, but I do get non-financial support and I am able to apply for grants, access free software and journals the institute is subscribing. I was told that’s similar to a tenure in US – you get your office and lab space, but little or no salary. But the difference would be that instead of applying for an independent position, you just take it :).

My income comes from grants and subcontracting other people projects. As a bioinformatician, I don’t have huge needs, so grants I applied for were pretty cheap compared to grants for experimental biology. However, it can take as long as half a year to a year to get an initial cash flow – it’s all about the time between a call and awarding the grant. Many times your degree doesn’t matter when applying for a grant, especially if you are not a principal investigator in the application. I still do not have a PhD degree, and while I hope to get one sometime this year (finally), I’m not pushing this that much.

Instead of carefully listing all good and bad sides of my freelancing status (or explaining reasons why I did such move) I will try to answer a question which I also hear often, which is: where is this heading?

In my probably skewed view of science to do things which are very novel and very cool one needs to be or a recognized genius, or a big shot in particular field. Otherwise, it’s hard to get enough money to fund one’s completely crazy projects. I’m neither a genius nor a big shot but I have bunch of ideas I consider cool and which I’d like to get funded. It looks like for that I need to step out of academic money-flow system, and apply for funding to people who are less conservative and who can take a risk of supporting non-established ideas (Deepak, thank you for the inspiration). And that’s the plan: leave academic (and competitive) funding system and shift to an outcome oriented one, similar in essence to a startup. And instead of waiting 15 years to get recognition in academia, I hope to get my stuff running within the next few years.

One can argue that it’s risky and one could achieve similar outcome following traditional academic career path within a similar time. Probably that’s true – all of the things I’ve just written are not really supported by long term evidence. But on the other hand, even if the whole idea doesn’t make sense at all, compared to my colleagues, I am having much more fun…

 
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Posted by on April 5, 2008 in Career

 

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