I am currently working on a doctorate in Social Work with interests in integrating a more science based approach to the field. I’m specifically interested in neuroscience and biological bases of mental illness and trauma.
I have a bit of a Biology background (I was a premed major before switching to social sciences as an undergrad), but I feel like I need more background to participate in biological research. I’m trying to figure out the best way to fill this educational gap (a Biology post bac, a grad certificate, another master’s degree in Biology).
Any suggestions on how to conduct research across fields?
I can only find evaluations/rankings for departments such as chemistry or physics, but I am not sure how to evaluate a combined program of chemical physics.
I am passionate about studying chemical physics and I would like to go to a university that has strong courses because I would like to have solid understanding. I would also like to do research with good professors. All the websites that have rankings only rank by subjects such as chemistry or physics but I cant find a place that ranks “chemical physics”. I have looked up the ranking of physics and chemistry for Ohio state since the chemical physics program is a collaboration between both departments but I am not sure if this enough. I would also like to know how Ohio state in chemical physics compares to other places with the same program.
I am interested to study chemical physics and I would like to know the best university to pursue a PhD in this field.
Suppose one’s interests lie in applying computer science to multiple unrelated disciplines (to illustrate ‘unrelated’ let’s take economics, music technology, medicine as examples). Suppose also that one is capable of publishing research outputs in each of those disciplines in its on right, either as sole author or more often collaborating with domain specialists.
The most logical home for all that activity would be a computer science department, as computing is the common thread linking all the work, and with a CS skill set you’d be able to teach CS undergrad topics and bring a lot of experience to the table with respect to applying computing to other fields.
One disadvantage of this approach however is that the research output would likely not be particularly innovative CS in its own right, as the focus is on application.
Another disadvantage in the UK (possibly elsewhere) may relate to REF: the journals you publish in may not help a CS department with its REF return if they fall outside of its chosen Unit of Assessment (i.e. they’re in the ‘wrong’ subject, especially for subjects where lower journal impact factors are the norm).
Given these limitations is it possible to succeed as an academic on this path, either in the UK or internationally? How can the challenges be addressed and are there other challenges I’m missing?
I’m looking for a list of journals that regularly publish survey papers in their field, but also for ways in which people optimize for getting a feel of the unfamiliar field. Survey papers are increasingly growing in importance in response to greater need for inter-disciplinary collaboration.
I have an undergraduate science degree as well as a doctorate in science. (for background: as part of my post-doctoral research, I have collaborated with authors from science to business to sociology).
About four years ago, I’ve started studying philosophy on my own, as a personal interest/hobby. Never being formally enrolled in a philosophy degree, I read extensively from books / papers / journals on continental philosophy.
More recently I have decided to take the plunge and tried exploring one of my doctoral research subtopics, but from a philosophical angle. I made an attempt to write a single-authored paper in continental philosophy, which to my delight, was accepted and presented at a national conference. Since then, I have another piece of (again single-authored) work pending review / acceptance at another conference, which is again closely related to one of my subtopics. So, as it turns out, my hobby of philosophy could be combined with my original area of academia.
Q: Can I, then, be considered a “philosopher”
(a) amongst the sciences; and/or
(b) amongst the humanities…
…when it comes to describing my recent contributions to the discipline. Or, should I introduce my work as ‘science with classical philosophical knowledge’? (It is tricky, as philosophy evolved from being a hobby, so to speak, to becoming a practical area of research that would help in my career).
I am at the beginning of my Ph.D. My research lies at the intersection of cognitive neuroscience and psycholinguistics, meaning that I will interact with a variety of researchers from several different fields – which should substantially broaden my horizons. However, reading the literature strictly related to those areas means I’m far less likely to keep track of developments in other areas, such as biology, physics, or computer science.
My question: how well aware should I be about major science developments that are not directly related to my area? How useful is this information for your own work?
I’m at the end of a 2 year post-Bacc at Columbia. My goal when I started was quite clear: I wanted to study atmospheric science through the lens of dynamical systems. However, as I’ve moved along, it’s become clear to me that my interest is really in the approach, and that I care relatively little about the particular field to which it is applied. That is: I’m much more interested in the process of modeling with dynamical systems than I am in what I’m modeling (though I would prefer to stay in the physical sciences). This is great in some senses, because it means that I can apply to a wealth of different sorts of programs, but I’m suffering from paralysis of choice; how can I even decide?
Some pertinent background:
-My undergraduate degree is actually in linguistics from Georgetown (it’s how I got interested in complexity science in the first place)
-I’ve been working with a research team in climate science, although it hasn’t been very mathematics heavy.
-My first project has begun to conclude, and so I’ve recently begun working with an physical oceanography research team doing very mathy stuff
-One of the theoretical climate scientists in the department (who started his career with a very theoretical fluid mechanics/dynamical systems approach) told me that the use of dynamical methods in atmospheric science has been largely mined out: there aren’t many tractable questions remaining and it will be difficult to find work doing that even if I do get funding for a PhD.
-My quantum mechanics professor recommended looking into either plasma physics or ion transport in batteries. She says these methods are being used there (and I trust her on this; she has her own lab doing work closely related to the later and is generally quite brilliant all the time).
I really need two things
a) Specific advice about how to navigate this choice and to finesse the applications: Are these fields all equally likely to allow me to play with these techniques? Should I be applying to math programs or science programs given my interests? Are there scientific fields I should consider beyond those recommended to me above (p. oceanography, atmospheric science, plasma).
b) General advice about organizing this choice, selling myself as a legit candidate in a diversity of fields (my background is at this point equivalent to a bachelors in Mathematical Physics kinda; more analysis than most physicist undergrads but less calculations.
So I am a Master of Science, majored in math, as of now. I am going to a reasonably good US university as an international student to get my PhD, which will likely be in probability, my main field of interest. I have heard a lot about how probability has applications in non-academic jobs and was wondering what would be my job prospects (in research and development) with such a PhD? I am not interested in purely academic research job.
I would like to add that I will be taking CS courses (lots of modelling courses especially), so I can bridge the gap between my knowledge of the purer side of math and its more applied side.